WSEAS Transactions on Systems
WSEAS Transactions on Systems
Print ISSN: 1109-2777
Volume 12, 2013
Issue 1, Volume 12, January 2013
Special Issue: Recent Advances in Control of Distributed Complex Physical Systems Applications, Methodology, Technology
Title of the Paper: Performance Enhancement of Continuous-Phase Modulation Based OFDM Systems Using Chaotic Interleaving
Authors: Emad S. Hassan
Abstract: In this paper, we propose a chaotic interleaving scheme for continuous-phase modulation based orthogonal frequency-division multiplexing (CPM-OFDM) systems. The idea of chaotic maps randomization (CMR) is exploited in this scheme. CMR generates permuted sequences from the sequences to be transmitted with lower correlation among their samples, and hence a better bit error rate (BER) performance can be achieved. The proposed CMR-CPM-OFDM system combines the advantages of frequency diversity and power efficiency from CPM-OFDM and performance improvement from chaotic interleaving. The BER performance of the CPM-OFDM system with and without chaotic interleaving is evaluated by computer simulations. Also, a comparison between chaotic interleaving and block interleaving is performed. Simulation results show that, the proposed chaotic interleaving scheme can greatly improve the performance of CPM-OFDM systems. Furthermore, the results show that the proposed chaotic interleaving scheme outperforms the traditional block interleaving scheme for CPM-OFDM systems. The results show also that, the proposed CMR-CPM-OFDM system provides a good trade-off between system performance and bandwidth efficiency.
Keywords: Chaotic interleaving, Frequency-Domain Equalization (FDE), Continuous-Phase Modulation (CPM), OFDM
Title of the Paper: Smart Grid Technology, Vision, Management and Control
Authors: Mohamed Zahran
Abstract: Energy supply has become one of the most challenging issues facing the world in the 21st Century. Growing populations, more homes and businesses and a myriad of new appliances have caused energy demand to skyrocket in every part of the country. The fundamental method of operating the nation’s power grid has not changed much in the past 100 years. It has remained essentially the same, although the number of customers and their needs have grown exponentially. Utilities across the nation and indeed, around the world are trying to figure out how to bring their networks into the 21st century and the digital age. This effort to make the power grid more intelligent is generally referred to as creating a “smart grid” The industry sees this transformation to a smart grid improving the methods of delivery as well as consumption. In the paper the state of the art of “smart grid” and its applications are introduced. The title is handled starting from the energy problems, growth in Egypt particularly and in the world generally were touched. The smart grid definition, benefits, advantages, problems as well as the smart grid vendors was introduced. A real implementation of smart grid technologies around the world as well as in Egypt is illustrated. In this paper many recent references and technical reports issued from authorized agencies are studied and presented. The international and governmental committees recommend the smart grid as smart solution for energy generation, transmissions, consumption and cost estimation.
Keywords: Smart grid, renewable energy sources, future energy systems, smart grid technology, vision of smart grid, distributed energy systems
Title of the Paper: Fuzzy-Logic Based Self-tuning PI Controller for High-Performance Vector Controlled Induction Motor Fed by PV-Generator
Authors: Ahmed M. Kassem
Abstract: In this paper, speed control of asynchronous machine fed by a photovoltaic (PV) generator based on a direct proportional and integral controller and an adaptive fuzzy logic controller (AFLC) is presented. Also In this study, it is proposed that the PV output voltage is varies between certain cut in and cut off values that to extract maximum power during different insolation values instead of operating the motor with constant voltage. To decrease the system cost, it is proposed that the system does not contain storage batteries and there is no needing for DC/DC converter where, variable voltage of PV generator is considered. The motor speed is controlled to track a certain reference values using the proposed controller. In addition, an efficient vector controller that can achieve high accuracy and a fast dynamic response of induction machine is presented. Also, In order to validate the effectiveness of the proposed adaptive fuzzy PI (AFPI) controller scheme, the performance of the proposed controller was compared with a classical PI controller. Obtained simulation results show that accurate tracking performance of the induction motor is achieved with variations of both PV generator output voltage and the load torque.
Keywords: Photovoltaic generator; Vector control; Adaptive control; Fuzzy logic control; PI control; Induction motor
Title of the Paper: Spectrum Sensing and Power Efficiency Trade-off in Cognitive Radio Networks over Fading Channels
Authors: Emad S. Hassan
Abstract: Multiple secondary users can cooperate to increase the reliability of spectrum sensing in cognitive radio networks. However, the total transmission power grows approximately linearly with the number of cooperative secondary users. This paper proposes a new approach to optimize the trade-off between sensing reliability and power efficiency in cooperative cognitive radio networks over fading channels. We assume K cooperative secondary users each collect N samples during the sensing time. The proposed approach is based on dividing the spectrum sensing into two phases. In the first phase, we use only n of N samples, (n ? N) to check the channels state, then k of K cooperative secondary users, (k ? K) which are in deeply faded channels are discarded. We call this n a check point of the sensing time. The spectrum sensing with relatively less-faded channels are continued during the second phase. Therefore, there is a check point at which the sensing time can be optimized in order to maximize the probability of detection and the power efficiency. Several experiments are carried out to test the performance of the proposed approach in terms of detection probability and power efficiency. The obtained results show that the proposed approach enhances the detection probability as well as it shortened the optimal sensing time. Moreover, it improves the overall power efficiency.
Keywords: Cognitive radio, cooperative spectrum sensing, power efficiency
Title of the Paper: Bacteria Foraging: A New Technique for Optimal Design of FACTS Controller to Enhance Power System Stability
Authors: E. S. Ali, S. M. Abd-Elazim
Abstract: This paper proposes Bacteria Foraging Optimization Algorithm (BFOA) based Static Var Compensator (SVC) for the suppression of oscillations in a multimachine power system. The proposed design problem of SVC over a wide range of loading conditions is formulated as an optimization problem with an eigenvalue based objective function. BFOA is employed to search for optimal controller parameters. The performance of the proposed technique has been evaluated with the performance of Genetic Algorithm (GA) to demonstrate the superior efficiency of the proposed BFOA in tuning SVC controller. Simultaneous tuning of the Bacteria Foraging based SVC (BFSVC) gives robust damping performance over a wide range of operating conditions in compare to optimized SVC controller based on GA (GASVC).
Keywords: SVC; Multimachine Power System; Genetic Algorithm; Bacteria Foraging; D- Shape
Issue 2, Volume 12, February 2013
Special Issue: Recent Methods on Physical Polluting Agents and Environment Modeling and Simulation
Title of the Paper: An Introduction to the Special Issue on Recent Methods on Physical Polluting Agents and Environment Modeling and Simulation
Authors: Claudio Guarnaccia, Filippo Neri
Title of the Paper: Measurements of Atmospheric Pollutants (Aromatic Hydrocarbons, O3, NOx, NO, NO2, CO, and SO2) in Ambient Air of a Site Located at the Northeast of Mexico during Summer 2011
Authors: J. G. Ceron-Breton, R. M. Ceron-Breton, E. Ramirez-Lara, L. Rojas-Dominguez, M. S. Vadillo-Saenz, J. L. Guzman-Mar
Abstract: Volatile organic compounds (aromatic hydrocarbons: benzene, ethyl benzene and p-xylene), O3, NO2, NO, NOX, CO, SO2 and meteorological parameters were measured in ambient air of a site located in the Metropolitan Area of Monterrey, Mexico. A total of 69 samples were collected for aromatic hydrocarbons and analyzed by Gas Chromatography with Flame Ionization Detection (GC-FID). Criteria pollutants concentrations were determined by automatic analyzers and meterological parameters were measured by a portable meteorological station. A marked diurnal variation was found for the three measured aromatic hydrocarbons. The highest concentrations occured during the morning sampling period (from 09:00 to 10:30 h) followed by the midday sampling period (from 12:00 to 13:30 h) and showing the lowest concentrations during the afternoon sampling period (from 15:00 to 16:30 h). Mean concentrations for benzene, ethyl benzene and pxylene were: 0.9, 1.06 and 1.63 μg m-3, respectively. Aromatic hydrocarbons abundance showed the following order: p-xylene > ethyl benzene > benzene. All criteria pollutants showed concentration values lower than the maximum permissible values requested by the air quality Mexican standards, only ozone showed levels approaching to the standard value. A relation among criteria pollutants, meteorological parameters and aromatic hydrocarbons was found using a Principal Compound Analysis (PCA), identifying some associations among the pollutants originated in common sources. Air pollutants maximum concentrations were found when winds blowed from NE. Important industrial sources and avenues with high vehicular traffic are located in this direction. These sources could contribute to the levels measured in the studied site. This site did not show a clear pattern of VOC’s/NOX sensitiviness to ozone formation during the study period.
Keywords: Volatile organic compounds, Aromatic hydrocarbons, Air pollutants, Monterrey, Mexico, Principal Compound Analysis, Ozone
Title of the Paper: Air Pollution Study of Vehicles Emission In High Volume Traffic: Selangor, Malaysia As A Case Study
Authors: Ahmad Fadzil Ahmad Shuhaili, Sany Izan Ihsan, Waleed Fekry Faris
Abstract: In an internal combustion engine, a chemical reaction occurs between the oxygen in air and hydrocarbon fuel. Engines operate at what is termed the stoichiometric air/fuel ratio when there is the correct quantity of air to allow complete combustion of the fuel with no excess oxygen. In reality, the combustion process cannot be perfect and automotive engines emit several types of pollutants.Therefore, it is important to develop and deploy methods for obtaining real-world, on-road micro-scaled measurements of vehicle emissions to estimate the pollutants. In this work, several high traffic roads in Selangor will be selected for the road air-quality measurement and analysis. Comparisons with simulations results, using the Operational Street Pollution Model (OSPM) are shown. The study shows that there were no serious of air pollution recorded in the period of January 2012. Air quality trends for the criteria pollutants in this month generally are continuing to show downward trends or stable trends well below the level of the Malaysian Ambient Air Quality Guideline (RMG). However, PM10 and ground-level O3 are the crucial pollutants in Selangor. The comprehensive review has revealed that moving vehicles creates a significant impact in air quality on the specific locations. Comparison with simulated data also showed good agreement thus indicating suitability of the model to be used in Malaysia condition.
Keywords: Air Pollution, Vehicles Emission, Air Polution Modeling, OSPM
Title of the Paper: Using Radon-222 as a Naturally Occurring Tracer to Investigate the Streamflow-Groundwater Interactions in a Typical Mediterranean Fluvial-Karst Landscape: The Interdisciplinary Case Study of the Bussento River (Campania Region, Southern Italy)
Authors: Michele Guida, Domenico Guida, Davide Guadagnuolo, Albina Cuomo, Vincenzo Siervo
Abstract: The Bussento river basin, located in the south-east of Campania region, shows interesting issues related to water assessment and management. Complex interactions and exchanges between surface and groundwater exist, influencing also on-shore and off-shore submarine springs. Therefore, gaining river segments from karst groundwater and losing river segments towards the aquifer are recognized. Groundwater protection for drinking domestic use, riverine wild-life conservation and coastal water quality require a progressively optimized knowledge of these interactions. As a support for hydrological modelling tasks, various measurement campaigns have been made along the Bussento river for the acquisition of data about Radon concentration in the river and spring waters, using a radon monitor, Rad7 (Durridge Inc.) , equipped with a water probe and a Rad7H2O to measure radon activity concentration in water. The aim of this preliminary study is to perform an useful methodology for the localization of the contributions of the groundwater along the riverbed, and for their proportional assessment compared with the superficial back return flow.
Keywords: Radon, Groundwater, Fluvial Karst Landscape, Hydro-geomorphology, River Drainage Basin
Title of the Paper: Assessment and Mapping of Radon-prone Areas on a regional scale as application of a Hierarchical Adaptive and Multi-scale Approach for the Environmental Planning. Case Study of Campania Region, Southern Italy
Authors: Domenico Guida, Michele Guida, Albina Cuomo, Davide Guadagnuolo, Vincenzo Siervo
Abstract: Nowadays, it is well established, among the international scientific community, that inside dwellings the largest contribution to the indoor Radon levels is provided by the source of the exhalated Radon, produced both directly from the soil located underneath the buildings and from the neighbour soils. This shared awareness has induced many European public institutions, responsible in matter of public health, to issue directives aimed at the assessment of the potential Radon exhalation from the soils, at regional scale, in order to achieve a planning of the radiogenic risk both in the residential buildings and in the working places. However, on one side, the lack of consolidated methodologies and procedures, shared among the experts’ community, has produced a valuable intense investigation research activity; on the other one, it led to the developing of different procedures, starting from diversified approaches. Synthetically, they can be classified according to the following typologies: i) indoor Radon measurements campaign-based approaches, ii) geology-based and geology-indoor correlation based, and iii) integrated ones. On the base of this last approach, the authors have started an interdisciplinary research program with contributions from Geology, Geomorphology, Soil Science, Environmental Physics, Building Engineering and Radiology and Epidemiology aimed to the development of a standard methodology, based on a multi-scale hierarchical (regional - provincial - sector- zone site) procedure of assessment of the Radon exhalation from soils. Such a procedure exploits an integrated, adaptive, approach to the problem as it requires the use of techniques of analysis, which are differentiated at the different scales of the territorial surveys and analysis. At the same time, they are interactive and progressively more deepened and more specific, from the regional to the zone mapping and modelling at the scale of a single site. The research is supported by a built-in database about Campania Region, consisting of both suitable territorial informations and experimental data provided by Radon activity concentration measurements in soil-gas performed in several sites and indoor measurements, integrated in a GIS-based management procedure. For its properties, this interdisciplinary multiscalar hierarchical adaptive approach can be successfully applied in many environmental studies and analysis. An interdisciplinary hierarchical multiscalar and adaptive methodology like the one described in this paper turns out to be a very powerful tool in many environmental and territorial planning approaches, especially wherever a “vast area” approach is needed to the environmental issues, i.e., the case of the urban acoustical or the electromagnetic pollution zoning. The “vast area” is an emerging concept and it regards a systemic approach to urban and regional planning methodology of analysis, design and management. Integration is pursued between the contributions given by the various disciplines involved in the planning process.
Keywords: Environmental Planning, Environmental Radioactivity, Radon Prone-Areas, Radon soil-gas, GIS maps
Title of the Paper: Advanced Tools for Traffic Noise Modelling and Prediction
Authors: Claudio Guarnaccia
Abstract: Environmental impact studies are strongly related to road traffic noise, especially in urban areas. A long term exposure to road traffic noise, in fact, can lead to relevant effects, both auditory (e.g. sleep disturbance, hearing loss, etc.) or not auditory (e.g. stress, anxiety, cardiovascular problems, etc.). A proper modelling of noise production and propagation is a challenging issue, especially in areas where the complexity of sources, receivers and other objects makes difficult to use standard predictive formulas, such as the usual Traffic Noise predictive Models (TNMs). The collection of experimental data is always advisable, in order to control the predictive tools and eventually tune their parameters. In this paper, the author presents a set of advanced tools for noise modelling, particularly aimed at the prediction of non-conventional situations, such as road intersections, traffic jams, extreme traffic flow, etc., where the standard TNMs usually fail. The main idea is to implement a dynamical approach in the traffic noise prediction, i.e. to include the dependence of noise emission by kinematical parameters, such as speed, position and eventually acceleration. This can be achieved by means of different approaches, some of them resumed in the paper, for instance cellular automata, traffic theory (Fundamental Diagram), source power dependence from the speed, etc.. The implementation of these models in easy to use tools represents the new horizon in traffic noise prediction.
Keywords: Noise Control, Road Traffic Noise, Traffic Theory, Dynamical Models
Issue 3, Volume 12, March 2013
Title of the Paper: A Technique for Diagnosing Abnormalities in Intermittent Sound Emission Mechanisms Based on Dynamic Programming Matching
Authors: Teruji Sekozawa
Abstract: This paper proposes an acoustic diagnosis technique for detecting abnormalities in and deterioration of machines that emit intermittent sounds during operation. The effectiveness of this technique is demonstrated experimentally. Acoustic diagnosis is generally applied to continuous sounds by analyzing the power spectrum patterns of regular, periodic sounds emitted by rotating components. However, machines such as automatic teller machines (ATMs) emit intermittent, episodic sounds during operation, making it impossible to employ the same diagnosis techniques as those used for conventional, continuous sounds. The proposed technique enables intermittent acoustic abnormalities to be diagnosed. It achieves this by constructing two vector series that are polygonal chain approximations of the temporal changes in the pressure levels of the most characteristic frequencies of the acoustic emissions during normal operation (the “standard vector series”) and during inspection (the “measured vector series”). The technique employs dynamic programming (DP) matching to collate and compare the two vector series at standard intervals. The technique consists of the following six steps: (1) acquisition of the temporal changes in the pressure level, as acoustic data; (2) extraction of the diagnosis regions; (3) selection of relevant features using a polynomial expansion filter; (4) polygonal chain approximation of the acoustic waveforms by vector series; (5) collation of the resulting measured vector and standard vector series by DP matching; (6) diagnosis of abnormality by vector dissimilarity. This paper provides detailed descriptions of steps 3 to 6. Steps 3 and 5 are particularly notable: in step 3, the acoustic data are approximated as vectors in a polygonal chain using a Hermite polynomial and the relevant features are extracted; in step 5, the DP collation absorbs operational asynchronicities, thereby eliminating what has been the greatest impediment to intermittent sound diagnosis. The effectiveness of this method for localizing and diagnosing abnormalities is demonstrated experimentally by applying it to acoustic data from the paper-slip transport in an actual machine.
Keywords: Acoustic diagnosis, Intermittent sound, Automatic teller machines, Polynomial expansion filter, Polygonal chain approximation, Dynamic programming matching, Vector dissimilarity
Title of the Paper: New Approach to Memory Less Design and Look-Up-Table Realization for Low-Complexity Reconfigurable Digital FIR Filter Architectures
Authors: J. L. Mazher Iqbal, S. Varadarajan
Abstract: Low-complexity and high-speed digital finite impulse response (FIR) filter is widely used in various signal processing and image processing applications because of less area, low cost, low power and high speed of operation. This article presents optimum low-complexity, reconfigurable digital FIR filter architectures based on memory less design and look up table (LUT) realization. The memory less design uses computation sharing multipliers (CSHM) and binary based common sub-expression elimination (BCSE) method for different word length filter coefficients. The memory based LUT multiplier approach uses memory elements to store the sub set of products of the filter coefficients. The LUT based multiplier removes the need of decoders in the FIR filter design. Thus reduce hardware complexity of the proposed reconfigurable digital FIR filter architectures. In this article, we show that the proposed memory based LUT multiplier approach could be an area-efficient alternative to distributed arithmetic (DA) based design of FIR filter with the same throughput of implementation. Also the proposed novel reconfigurable FIR filter architecture using CSHM involves less area and lower latency of implementation compared to the existing reconfigurable FIR filter implementations.
Keywords: Memory-based computing, Common sub-expression elimination (CSE), Low-complexity, Reconfigurable architectures, VLSI
Title of the Paper: Dynamic Obstacle Avoidance for Path Planning and Control on Intelligent Vehicle Based on the Risk of Collision
Authors: Lu Yeqiang, Qiu Faju, Xin Jianghui, Shang Weiyan
Abstract: To improve the autonomy of intelligent vehicle in complex or uncertain environment, a dynamic planning control method for obstacle avoidance has been studied. By leading the degree of risk collision into control system as the input and using an improved fuzzy control algorithm, the input and output of the fuzzy controller can be considered as extract amount. The concept of patterns and pattern matching was used, and according to the matching degree of each rule, the weighted average algorithm was applied to determine the output of control action, this method can avoid a dynamic obstacle in a timely manner and shorten the computing time. At last, by simulation, it was verified that the dynamic control method can make intelligent vehicle avoid the dynamic obstacles independently, and walking toward the target point exactly. And the results also provide a theoretical basis for the realization of the intelligent vehicle moving independently and safely in the complex and dynamic environment.
Keywords: Intelligent vehicle, Degree of risk collision, Fuzzy control, Dynamic obstacle avoidance
Title of the Paper: Wavelets and Ridgelets for Biomedical Image Denoising
Authors: D. Mary Sugantharathnam, D. Manimegalai, B. Ganapathy Ram
Abstract: Image de-noising is a key step in the processing of medical images as they are often corrupted by noise in the process of receiving, coding and transmission. In this paper the performance of Discrete Wavelet Transform (DWT) (Bivariate shrinkage), Stationary Wavelet Transform (SWT) (hard thresholding), Dual Tree Complex Wavelet Transform (DTCWT) (Bivariate shrinkage) and Ridgelet Transform (Hard thresholding) for biomedical image de-noising are evaluated and compared in terms of Peak Signal to Noise Ratio (PSNR). The DWT in many applications reaches its limitations such as oscillations of coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. Therefore SWT and DTCWT, both with their shift invariant property are studied. DTCWT a moderately redundant multi-resolution transform with decimated sub bands runs into two DWT trees (real and imaginary) of real filters producing the real and imaginary parts of the coefficients. A locally adaptive de-noising algorithm using the bivariate shrinkage function is illustrated using both DWT and DTCWT. A simple bivariate shrinkage rule is described to model the statistics of wavelet coefficients of images. The Ridgelet transform was developed over several years to break the limitations of Wavelet Transform and possesses high directional selectivity. Simulations and experimental results demonstrate that the DTCWT outperforms SWT and DWT as well as Ridgelets in denoising biomedical images corrupted by Random noise, Salt and pepper noise and Gaussian noise while SWT outperforms other wavelet techniques and Ridgelets in de-noising biomedical images degraded by Speckle noise and Poisson noise.
Keywords: De-noising, Wavelet, Ridgelet, Bivariate shrinkage, Threshold
Title of the Paper: A FDH Study of the Vancouver 2010 Winter Olympic Games
Authors: Juliana Da Câmara Torres Benicio, Níssia Carvalho Rosa Bergiante, João Carlos Correia Baptista Soares De Mello
Abstract: Many authors have been used different mathematical models to study the results of the Olympic Games. Some of these studies try to find new ways to establish alternative performance rankings while others evaluate the efficiency of the countries participating to the competition. Some use economics variables as inputs, others, included social aspects but in general, all of them chose the output orientation. In this work we are interested in studying the results of the Winter Olympic Games, held in Vancouver, Canada in 2010. We choose FDH (Free Disposal Hull) model but we decided to use input orientation. We brought into account the number of athletes of each country as input. As outputs, we use the number of gold, silver and bronze medals. The unit of analysis will be all the countries that took part in the games, even though they had not won any medals.
Keywords: Winter Olympic Games, FDH model studies, BCC model
Issue 4, Volume 12, April 2013
Title of the Paper: Adaptive Noise Filtering of Image Sequences in Real Time
Authors: Ali M. Reza
Abstract: Filtering noise in image sequences is an important preprocessing task in many image processing applications, including but not limited to real-time x-ray image sequences obtained in angiography. The main objective in real-time noise filtering is to improve the quality of the resultant image sequences. Practically affordable approaches are generally suboptimal and deal with the spatial and temporal dimensions independently. Spatial filters can be adaptive and edge sensitive, however, they may require more hardware real estate for the real-time processing of each frame. On the other hand, temporal-only filters are one-dimensional and take advantage of temporal correlation. These 1-D temporal filters, which are applied to each individual pixel, can be designed using adaptive approaches to compensate for motions as well as noise variations. Existing adaptive 1-D filters are relatively complex and do not lend themselves to an affordable hardware implementation for real-time processing. In this article, after reviewing different filtering approaches, an adaptive temporal restoration algorithm, based on discrete Kalman filter, is developed. Adaptation in this case is with respect to the variation of the noise statistics as well as motion. In each step of the algorithm, the conventional adaptive Kalman filter proceeds if no motion is detected. However, in the case of detected motion, the adaptive Kalman filter resets itself in a way that the motion is preserved and cause no lagging in the processed image sequence. The overall procedure is suitable for hardware implementation with present FPGA/VLSI technology.
Keywords: Image Sequence Filtering, Temporal and Spatial Filtering, Adaptive Filtering, Kalman Filter
Title of the Paper: Air Defense Missile Detonation Delay Control Based on FPGA/DSP
Authors: Lian-Zheng Zhang, Pan-Long Wu, Xin-Yu Zhang
Abstract: This paper presents the hardware design of a real time tracking system based on DSP/FPGA regarding the research and air defense missile detonation delay. It is a new trend of missile technology using guidance integrated fuze (GIF) technology to realize optimal burst delay control algorithm. The optimal burst delay control algorithm includes the estimation of time-to-go and miss distance. The paper studied the application of second order debiased converted measurement Kalman (SDCMKF) filer in parameters estimation of burst delay control. In this tracking system, the FPGA is used as a floating point co-processor of the fixed point DSP, and the large amount of calculation of the second order debiased converted measurement Kalman Filter (SDCMKF) algorithm is realized in FPGA. DSP is in charge of the scheduling of the total tracking algorithm and the control of the data stream, which resolves the problem of the concurrency and real time in the realization of the single DSP scheme. The designed tracking system ensures the accuracy of the data processing as well. Simulation results indicate that the application of this algorithm improved the estimation accuracy of burst delay control. The estimation error reduces gradually and tends to be stable with the distance between target and missile shortened.
Keywords: Target tracking, air defense missile detonation delay, burst delay control, SDCMKF, coprocessor, FPGA, DSP
Title of the Paper: A Novel Hybrid Fuzzy Weighted Average for MCDM with Interval Triangular Type-2 Fuzzy Sets
Authors: Nurnadiah Zamri, Lazim Abdullah, Muhammad Suzuri Hitam, Noor Maizura Mohammad Noor, Ahmad Jusoh
Abstract: Weight plays an important role in multi-criteria decision making (MCDM), as it would have a deep effect on the evaluation results. Fuzzy weighted average is one of the popular weight in MCDM method. However, the inherent uncertainty of this method can result in weighting errors. Therefore, this paper presents an interval triangular type-2 fuzzy set (ITT2FS) to capture uncertainty in multi-criteria decision making (MCDM) problems. In this paper, a new weighted average is developed using the concept of interval triangular type-2 fuzzy sets. Based on the concept of the relative closeness coefficients, we construct a simpler interval triangular type-2 fractional programming in weighted average to calculate the closeness coefficients, which can be employed to generate the ranking order of alternatives. The proposed method is illustrated with three numerical examples. As a result, we found that the proposed method is practical for solving the type-2 fuzzy TOPSIS problems. Besides, it seems that the proposed method is flexible, easy to use and low computational volume. Moreover, it has acceptable accurate.
Keywords: Weighted average, Multiple attribute decision making, Interval type-2 fuzzy sets, Interval triangular type-2 fuzzy sets
Title of the Paper: The Attitude Control of the Four-Rotor Unmanned Helicopter Based on Feedback Linearization Control
Authors: Zhang Yaou, Zhao Wansheng, Lu Tiansheng, Li Jingsong
Abstract: This work is a contribution to stable attitudes control of the small scale four-rotor helicopter. The small scale four-rotor helicopter is a multi-variable strong coupling nonlinear system, especially its complicated attitude control. In order to control the attitude of the helicopter, the deliberate dynamics and kinematics of four-rotor helicopter attitude model was established. Based on the model derived, the feedback linearization method was utilized to decouple model and control the system. According to the characteristics of the attitude in the helicopter’s whole motion process, two control tasks were numerically performed, and the corresponding simulation results show that the proposed control strategy behaves remarkably well. This work also built the foundation for the position control of the helicopter.
Keywords: four-rotor helicopter, feedback linearization method, attitude control
Title of the Paper: Application of Adaptive MRF Based on Region in Segmentation of Microscopic Image
Authors: Lihong Li, Minglu Zhang, Yazhou Wu, Lingyu Sun
Abstract: According to the characteristics of microscopic image, an adaptive MRF method based on region is provided for segmentation of microscopic image. Based on a series of filtering and de-noising, morphological gradient is implemented for image. Then a watershed algorithm is used for image’s over-segmentation. In order to reduce the influence of noise, the mean gray value of regional block substitutes for each pixel value in this regional block. The fuzzy c-means algorithm is implemented for initial segmentation of image. In this processing, the mean value and variance of this region is feature value. Then MRF potential function is computed. Condition potential function is represented by membership of regional feature value on clustering center. The connection parameter of priori potential function is adaptively determined according to the connection degree between regional block and its adjacent blocks. The edge of the segmented regions with this algorithm is better than that algorithm in which fixed connection parameter is adopted. Because fuzzy c-means segmentation can get good initial state value, ICM with better real-time is employed to calculate the minimum potential function. Experiments show that this algorithm is better than OTSU, the traditional MRF and regional MRF with fixed connection parameter. This algorithm has better anti-noise ability and edge segmentation image. It has good robustness
Keywords: Segmentation of microscopic image, Markov random field based on region, Watershed, Adaptive connection parameter, image processing, potential function
Issue 5, Volume 12, May 2013
Title of the Paper: Multiple Observer Design for a Nonlinear Takagi-Sugeno System Submitted to Unknown Inputs and Outputs
Authors: Nasreddine Bouguila, Wafa Jamel, Atef Khedher, Kamel Ben Othman
Abstract: In this paper we focus on the state estimation of a nonlinear system described by a Takagi-Sugeno multiple model submitted to unknown inputs and outputs. The proposed approach consists on a mathematical transformation which enables to consider the unknown outputs as unknown inputs that can be eliminated by a designed multiple observer. To evaluate the efficiency of the proposed approach, the convergence conditions of the state estimation error are formulated as linear matrix inequalities (LMI). Simulation Examples are given to illustrate the proposed methods.
Keywords: Multiple model approach, multiple observer, state estimation, unknown inputs and outputs
Title of the Paper: An Expert System Based on Multi-Source Signal Integration for Reciprocating Compressor
Authors: Zhinong Jiang, Jinjie Zhang, Mengyu Jin, Bo Ma
Abstract: In refining, pipeline, and metallurgical enterprises, reciprocating compressor fault diagnosis is hard work and requires a high level of expertise; only a few experts have the ability to do the work. This paper describes an expert system (ES), which is designed to apply a composite diagnosis main structure based on multi-source signal integration for reciprocating compressor, for reciprocating compressor fault diagnosis. For automatically diagnosing 39 faults of the reciprocating compressor and other auxiliary system, the ES includes 67 facts and over 400 rules. The ES has been developed as part of an on-line monitoring system that has been used in various factories and successfully diagnosed many realistic faults.
Keywords: Reciprocating compressor, Fault diagnosis, Expert system, Composite diagnosis, Multi-source signal integration
Title of the Paper: Idiosyncratic Volatility Has an Impact on Corporate Bond Spreads: Empirical Evidence from Chinese Bond Markets
Authors: Su-Sheng Wang, Jie-Min Huang, Kai Chang, Jie-Yong Huang, Xi Yang
Abstract: In the paper we use panel data of weekly corporate bond yields dated from September 19th 2008 to June 1st 2012 in Shanghai and Shenzhen Stock Exchange, and the fixed effect model with variable intercept, to do empirical research. The factors which affect corporate bond spread mainly include bond market complex index, stock market complex index, CPI, bond idiosyncratic volatility and stock idiosyncratic volatility. As the research shows, the bond market complex index has strong positive effect on corporate bond spread but CPI has opposite effect on it. Additionally, stock market complex index exhibits some positive effects on corporate bond spread. And in contrast, bond idiosyncratic volatility and stock idiosyncratic volatility show some negative effects, which illustrates that idiosyncratic volatility, complex bond index, complex stock index and CPI have common effect on the corporate bond spread.
Keywords: Corporate bond, spreads, idiosyncratic volatility, bond complex index, stock complex index, CPI
Title of the Paper: State Dependent Riccati Equation Based Filtering and Control of a Magnetorheological Fluid Brake
Authors: Renato Brancati, Riccardo Russo, Mario Terzo
Abstract: A theoretical/experimental activity has been carried out on a magnetorheologicalfluid brake prototype. A non-linear observer and an optimal control have been designed andtested on the physical device. Both the feedback control and the state observer are based onthe state dependent Riccati equation technique.A first order non-linear dynamic model hasbeen derived and adopted for the development of the braking torque control system.Simulation results confirm the goodness of theproposed control scheme which effectivenesshas been evaluated by means of hardware in the loop tests.
Keywords: Measurement noise, Magnetorheological fluids, Kalman filter, Non-linear filtering and control
Issue 6, Volume 12, June 2013
Special Issue: Advanced Control Methods: Theory and Application
Title: An Introduction to the Special Issue on Advanced Control Methods: Theory and Application
Authors: Libor Pekař, Filippo Neri
Title of the Paper: Self-tuning Control of Non-linear Servomotor: Standard Versus Dual Approach
Authors: Vladimír Bobál, Petr Chalupa, Petr Dostál, Marek Kubalcík
Abstract: The majority of processes met in the industrial practice have stochastic characteristics and eventually they embody non-linear behaviour. Traditional controllers with fixed parameters are often unsuitable for such processes because their parameters change. The changes of process parameters are caused by changes in the manufacturing process, in the nature of the input materials, fuel, machinery use (wear) etc. Fixed controllers cannot deal with this. One possible alternative for improving the quality of control for such processes is the use of adaptive control systems. Different approaches were proposed and utilized. One successful approach is represented by self-tuning controller (STC). This approach is also called system with indirect adaptation (with direct identification). The main idea of an STC is based on the combination of a recursive identification procedure and a selected controller synthesis. Presently, most of the STCs are based on the Certainty Equivalence (CE) Principle, which is only suboptimal. One of the possibilities to improve the quality of these adaptive control methods is usage of an Adaptive Dual Control (the bicriterial approach). In this paper, the bicriterial approach is verified and compared with some other adaptive control approaches based on the CE Principle by the real-time control of a highly non-linear laboratory model, the DR300 Speed Control with Variable Load.
Keywords: Self-tuning control; Dual control; Bicriterial approach; ARX model; Recursive least squares; Non-linear system; Servo motor; Real-time control
Title of the Paper: Feedforward Model Based Active Force Control of Mobile Manipulator using MATLAB and MD Adams
Authors: Shariman Abdullah, Musa Mailah, Collin Tang Howe Hing
Abstract: The paper highlights the potentials of using a feedforward model based Active Force Control (AFC) as a disturbance rejection scheme in the motion control of a mobile manipulator (MM). The AFC part creates a force or torque feedback within the dynamic system to allow for the compensation of the sudden disturbance introduced into the system prior to relaying the signal to the conventional outerloop position controller employing a resolved acceleration control (RAC) configuration, thereby increasing the robustness of the MM system. The proposed AFC-based model also shows a faster computational performance by manipulating the estimated inertia matrix (IN) of the system instead of considering the entire system dynamic model. A feedforward element in the form of a simplified model of the dynamic system is implemented to complement the IN for a better trajectory tracking performance of the system. The simulation was performed and the results were compared with the computed torque control (CTC) with RAC scheme to benchmark the performance and robustness of the AFC-based counterpart. The MM consists of a skid steering four wheel nonholonomic mobile platform with a three degree-of-freedom (DOF) articulated manipulator attached on top. With the proposed controller incorporated into the system, the tracking performance of the MM is considerably enhanced with increased workspace capacity and better operation dexterity.
Keywords: Active force control, Feedforward model based control, Mobile manipulator, Robust control, Tracking Performance
Title of the Paper: On a Controller Parameterization for Infinite-Dimensional Feedback Systems Based on the Desired Overshoot
Authors: Libor Pekař
Abstract: The aim of this paper is to introduce, in detail, a novel approach for tuning of anisochronic singleinput single-output controllers for infinite-dimensional feedback control systems. A class of Linear Time- Invariant Time Delay Systems (LTI TDSs) is taken as a typical representative of infinite-dimensional systems. Control design to obtain the eventual controller structure is made in the special ring of quasipolynomial meromorphic functions (RMS). The use of this algebraic approach with a simple feedback loop for unstable or integrating systems leads to infinite-dimensional (delayed) controllers as well as the whole feedback loop. A natural task is to set tunable controller parameters in order to form the crucial area of the infinite closed-loop spectrum. It is worth noting that not only poles yet also zeros are taken into account. The prescribed positions of the right-most reference-to-output poles and zeros are given on the basis of the desired overshoot for a simple finite-dimensional matching model the detailed analysis of which is provided. The dominant poles and zeros are shifted to the prescribed positions using the Quasi-Continuous Shifting Algorithm (QCSA) followed by the use of an advanced optimization algorithm. The whole methodology is called the Pole-Placement Shifting based controller tuning Algorithm (PPSA). The PPSA is demonstrated on the setting of parameters of delayed controller for an unstable time delay plant of a skater on the controlled swaying bow. This example, however, shows a treachery of the algorithm and a natural feature of an infinite-dimensional system – namely, that its spectrum or even its dominant part can not be placed arbitrarily. Advantages and drawback as well as possible modification of the algorithm are also discussed.
Keywords: Infinite-dimensional systems, Time delay systems, Algebraic control design, Controller tuning, Pole-assignment, Pole-shifting, Desired overshoot, Optimization
Issue 7, Volume 12, July 2013
Special Issue: Advances on Interactive Multimedia Systems
Title: An Introduction to the Special Issue on Advances on Interactive Multimedia Systems
Authors: Z. Bojkovic, F. Neri
Title of the Paper: New Online RKPCA-RN Kernel Method Applied to Tennessee Eastman Process
Authors: Nadia Souilem, Ilyes Elaissi, Okba Taouali, Hassani Messeouad
Abstract: This paper proposes a new method for online identification of a nonlinear system using RKHS models. The RKHS model is a linear combination of kernel functions applied to the used training set observations. For large datasets, this kernel based to severs computational problems and makes identification techniques unsuitable to the online case. For instance, in the KPCA scheme the Gram matrix order grows with the number of training observations and its eigen decomposition. The proposed method is based on Reduced Kernel Principal Component Analysis technique (RKPCA), to extract the principal component will be time consuming.
Keywords: RKHS, RN, SLT, Kernel method, RKPCA, Online RKPCA-RN, Tennessee.
Title of the Paper: Methods and Tools for Structural Information Visualization
Authors: V. N. Kasyanov
Abstract: In the paper, we consider a practical and general graph formalism called hierarchical graphs and graph models. It is suited for visual processing and can be used in many areas where the strong structuring of information is needed. We present also the Higres, Visual Graph and ALVIS systems that are aimed at supporting of structural information visualization on the base hierarchical graph modes.
Keywords: Information visualization, Hierarchical graphs, Hierarchical graph models, Graph algorithm animation, Graph editor, Graph drawing, Graph visualization, Visualization system
Title of the Paper: Recognition of Assamese Spoken Words using a Hybrid Neural Framework and Clustering Aided Apriori Knowledge
Authors: Pallabi Talukdar, Mousmita Sarma, Kandarpa Kumar Sarma
Abstract: In this paper, an Artificial Neural Network (ANN) based model is proposed for recognition of discrete Assamese speech using a Self Organizing Map (SOM) based phoneme count determination technique. The phoneme count determination technique takes some initial decision about the possible number of phonemes in the word to be recognized and accordingly the word is presented to some N-phoneme recognition algorithm. In this paper recognition algorithm is designed to recognize three phoneme consonant-vowel-consonant (CVC) type Assamese words. The word recognizer is consisted of another SOM block to provide phoneme boundaries and Probabilistic Neural Network (PNN) and Learning Vector Quantization (LVQ) to identify the SOM segmented phonemes. The recognition of constituent phonemes in turn represents the discrimination between incoming words with a minimum success rate of 90%.
Keywords: Formant, Phoneme, ANN, KMC, LPC, DWT.
Title of the Paper: Fuzzy Authentication Algorithm with Applications to Error Localization and Correction of Images
Authors: Obaid Ur-Rehman, Natasa Zivic
Abstract: Images are normally protected using standard messages authentication codes to protect them against tampering and forgeries. One problem with this approach is that when such images are transmitted over a noisy medium, even a single bit error might render the image as un-authentic to the receiver. In this paper, a noise tolerant data authentication algorithm is proposed. The proposed algorithm can perform authentication in the presence of minor errors but at the same time identify forgeries in the data. This algorithm is then extended by demonstrating its applications in image authentication. The extended algorithm is called as fuzzy authentication algorithm. It has the ability to localize errors in an image as well as correct the localized errors using error correcting codes. The proposed algorithm rejects only the potentially erroneous / unauthentic parts of the image and correct or authenticate the remaining parts if the number of errors is below a certain threshold. This reduces the need for retransmission of the complete image and only a few parts might be retransmitted if the application demands. This property is especially useful in real-time communications. It is better to obtain a part of the authentic image, rather than having no image at all. A security analysis of the proposed algorithm is given, and simulation results are presented to demonstrate its error localization and correction capabilities.
Keywords: Fuzzy Authentication; Image Authentication; Reliability Values; Soft Authentication; Content Based Authentication; Noise Tolerant Authentication
Issue 8, Volume 12, August 2013
Title of the Paper: Fault Tolerant Model Predictive Control of Three-Phase Permanent Magnet Synchronous Motors
Authors: Qingfang Teng, Jianyong Bai, Jianguo Zhu, Yunxia Sun
Abstract: A new fault tolerant model predictive control (FTMPC) strategy is proposed for three-phase magnetically isotropic permanent magnet synchronous motor (PMSM) with complete loss of one phase (LOP) or loss of one leg (LOL) of the inverter. The dynamic model of PMSM with LOP or LOL is derived in abc- System. The principle of FTMPC is investigated, its predictive model for remaining two stator phase currents is established after LOP or LOL occurs, and the flux estimator based on current model is employed in order to calculate the stator flux & its corresponding torque. Extra-leg extra-switch inverter is used as power unit. The PI controller is put to use for regulating rotor speed and generating reference torque. Dynamic responses of healthy MPC and unhealthy FTMPC for PMSM systems are given to compare their performance via simulation and some analysis is presented. The simulation results show that the proposed FTMPC strategy not only allows for continuous and disturbance-free operation of the unhealthy PMSM with LOP or LOL but also preserves satisfactory torque and speed control. And then the effectiveness of the proposed schemes in this paper is demonstrated.
Keywords: Fault tolerant control; Model predictive control; Permanent magnet synchronous motor; Motor model; Flux estimator; Inverter
Title of the Paper: Knowledge-based Mill Fan System Technical Condition Prognosis
Authors: Lyubka Doukovska, Svetla Vassileva
Abstract: The task of diagnosis is to find an explanation for a set of observations and – in the case of prognosis – to forecast the course of events. Diagnosis can be broken down into anomaly detection and failure identification, depending on the desired granularity of information required. Prognosis is concerned with incipient failure detection, margin prediction, or overall performance prediction. The latter can be prediction of efficiency, current system status, etc. The outcome of diagnosis and prognosis processes drives planning and execution. Fault isolation task can only be realized if the fault to be isolated has been previously taken into account in the model. There are different approaches for the design of diagnostic observers: the geometric methods, algebraic methods, spectral theory-based methods and frequency domain solutions. In our paper a two-step procedure is commonly employed for data-driven fault detection. A model that represents the normal operation conditions is first developed; then fault detection is carried out according to the residual information or according the differences in the quality parameters of the transient process. The data-based models, usually black-box models, lie in the core of a modular diagnosis system concept which has been chosen as separate fault detection systems. Each of these systems is handling only partial information on the process. This is similar to different persons analyzing the same situation with different methods and/or different sources of information. In the paper are presented the studied industrial mill fan, models of the studied systems and corresponding controller design by implementing conventional and fuzzy logic-based approaches. Simulation results – transient processes in the closed loop are implemented for the knowledge-based fault detection and prognosis.
Keywords: Knowledge-based Fault Detection, Fault Diagnostic, Fault prognosis, Mill fan, Fuzzy Logic Controller design
Title of the Paper: The Term Structure Model of Corporate Bond Yields
Authors: Jie-Min Huang, Su-Sheng Wang, Jie-Yong Huang
Abstract: We build the term structure of corporate bond yields with N-factor affine model, and we estimate the parameters by using Kalman filtering. We choose weekly average corporate bond yields data in Shanghai Stock Exchange and Shenzhen Stock Exchange. We find the one-factor model and two-factor model could do one-step forward forecasting well, but the three-factor model could fit the observable data well.
Keywords: Corporate bond; yields; term structure; Kalman filtering
Issue 9, Volume 12, September 2013
Title of the Paper: Research on Direct Power Control of Modular Multilevel Converter Based VSC-HVDC for Offshore Wind Farm
Authors: Xingwu Yang, Guoqiang Wang
Abstract: Control methods for novel modular multilevel converter (MMC) were studied and applied to voltage source converter based HVDC (VSC-HVDC) for offshore wind farm. The system output characteristics under different modulation methods were analyzed. Different balancing control methods of sub-module (SM) capacitor voltage were designed for n+1 and 2n+1 level output respectively, then the generation principles of 2n +1 level were described in detail. Two DC output ways for MMC which are with and without additional DC capacitors were compared. The simulation results showed that the 2n+1 MMC with additional DC capacitors had better performance and was more suitable for VSC-HVDC system. Meanwhile, the strategy of virtual flux direct power control (VF-DPC) was applied for MMC focusing on the power estimation method of this topology. The control method designed in this paper was compared with the traditional strategy of double closed loop vector control and the results showed that the control system of this paper possessed better dynamic response. Finally, MATLAB was used for testing under various conditions, the results show that the designed method is correct and effective.
Keywords: Direct power control, MMC, modulation method, offshore wind farm, VSC-HVDC
Title of the Paper: J-measure Based Hybrid Pruning for Complexity Reduction in Classification Rules
Authors: Han Liu, Alexander Gegov, Frederic Stahl
Abstract: Prism is a modular classification rule generation method based on the ‘separate and conquer’ approach that is alternative to the rule induction approach using decision trees also known as ‘divide and conquer’. Prism often achieves a similar level of classification accuracy compared with decision trees, but tends to produce a more compact noise tolerant set of classification rules. As with other classification rule generation methods, a principle problem arising with Prism is that of overfitting due to over-specialised rules. In addition, over-specialised rules increase the associated computational complexity. These problems can be solved by pruning methods. For the Prism method, two pruning algorithms have been introduced recently for reducing overfitting of classification rules - J-pruning and Jmax-pruning. Both algorithms are based on the J-measure, an information theoretic means for quantifying the theoretical information content of a rule. Jmax-pruning attempts to exploit the J-measure to its full potential because J-pruning does not actually achieve this and may even lead to underfitting. A series of experiments have proved that Jmax-pruning may outperform J-pruning in reducing overfitting. However, Jmax-pruning is computationally relatively expensive and may also lead to underfitting. This paper reviews the Prism method and the two existing pruning algorithms above. It also proposes a novel pruning algorithm called Jmid-pruning. The latter is based on the J-measure and it reduces overfitting to a similar level as the other two algorithms but is better in avoiding underfitting and unnecessary computational effort. The authors conduct an experimental study on the performance of the Jmid-pruning algorithm in terms of classification accuracy and computational efficiency. The algorithm is also evaluated comparatively with the J-pruning and Jmax-pruning algorithms.
Keywords: Data Mining, Machine Learning, Classification Rules, J-pruning, Jmax-pruning, Jmid-pruning, if-then rules, overfitting, J-measure
Title of the Paper: An Improved PSO Clustering Algorithm Based on Affinity Propagation
Authors: Yuyan Zheng, Jianhua Qu, Yang Zhou
Abstract: Particle swarm optimization (PSO) is undoubtedly one of the most widely used swarm intelligence algorithm. Generally, each particle is assigned an initial value randomly. In this paper an improved PSO clustering algorithm based on affinity propagation (APPSO) is proposed which provides new ideas and methods for cluster analysis. Firstly the proposed algorithm get initial cluster centers by affinity propagation. Secondly obtained initial cluster centers are regarded as inputs of one of all particles instead of being assigned randomly. Finally we cluster with the improved PSO clustering algorithm. Through experiment test, we demonstrate that the improved PSO clustering algorithm has not only high accuracy but also certain stability.
Keywords: Particle Swarm Optimization (PSO); Affinity Propagation Clustering; Clustering Algorithm
Issue 10, Volume 12, October 2013
Special Issue: Orbital Dynamics and Spacecraft Attitude Control
Title of the Paper: An Introduction to the Special Issue on Orbital Dynamics and Spacecraft Attitude Control
Authors: C. F. de Melo, F. Neri
Title of the Paper: The Brazilian Autonomous Star Tracker - AST
Authors: Antonio Gil V. De Brum, Márcio A. A. Fialho, M. L. Selingardi, Nilton D. Borrego, José L. Lourenço
Abstract: The main subject of this paper is the star tracker system called AST (autonomous star tracker), currently under development at the Brazilian National Institute for Space Research – INPE. A description of the approach used to estimate the attitude on board the spacecraft, in real time and autonomously, is presented. The methods and techniques described in this paper guided the creation of the embedded software of the instrument in what concerns the attitude estimation and tracking. In it, a pattern recognition procedure is employed to identify stars in the field of view (FOV) of an active pixel sensor (CMOS APS), which comprises a star sensor system of one fixed head. As results, two computer program packages were created. The first one is intended to control the star tracker system operation, and the other is a simulation environment to test the system operation. This simulator environment was called ADAST (Attitude Determination Algorithm Software Test) and it represents an important contribution to the sector, for it comprises a complete simulation environment of a star sensor/tracker system, to be used in both, the understanding of the fundamentals of this equipment operation, and in the design and testing of algorithms that make up the system. The part of the studies concerning the search and track operations, along with their results, are discussed and presented in this paper. Some tests of the AST system are scheduled and are also described. Once tested, the AST will integrate the attitude control system of future Brazilian satellites within the goals of the space program in progress.
Keywords: Brazilian satellite, autonomous star tracker, AST, ADAST, attitude estimation software
Title of the Paper: Exact Solutions in Attitude Dynamics of a Magnetic Dual-Spin Spacecraft and a Generalization of the Lagrange Top
Authors: Anton V. Doroshin
Abstract: The present paper contains an investigation results for the attitude motion of a magnetic dual-spin spacecraft (DSSC) in the geomagnetic field at the realization of the orbital motion of its mass center along an equatorial circular orbit. Exact analytical solutions for the attitude motion parameters are obtained in the elliptic Jacobi functions including the angular momentum components, the directional cosines and the Euler angles. These analytical exact solutions correspond to generating dependences which make possible the advanced research of the DSSC perturbed motion cases. The considering task of the DSSC angular motion can be characterized as the Lagrange top generalization for the coaxial bodies system – the corresponding case of the magnetic DSSC motion occurs under the influence of external restoring/overturning torques (like in the Lagrange heavy top motion). This paper's results also can be directly reduced to the Euler coaxial top's (Euler's case of the rigid body and coaxial bodies motion) general exact explicit solutions; this circumstance can be consider as a generalization of the Euler coaxial top's problem. An important “dynamical equivalence” between the magnetic and gyroscopic DSSC attitude stabilization factors is illustrated.
Keywords: Magnetic Dual-Spin Spacecraft, Explicit Solutions, Jacobi Functions, Lagrange top, Euler top
Title of the Paper: An Object-Oriented Analysis and Design Model to Implement Controllers for Quadrotor UAVs by Specializing MDA’s Features with Hybrid Automata and Real-Time UML
Authors: Diem P. G., Hien N. V., Khanh N. P.
Abstract: This paper presents a new approach which is based on the specialization of the Model-Driven Architecture (MDA) with the Real-Time Unified Modeling Language (RT UML) and hybrid automata to effectively analyze, design and implement controllers for quadrotor UAVs (Unmanned Aerial Vehicles). It also allows the designed elements to be customizable and re-usable in the development of new control applications of different quadrotor UAVs. The paper shows out step-by-step the quadrotor UAV dynamic model-to-be used, and the specialization of MDA’s features such as the Computation Independent Model (CIM) with use-cases and hybrid automata, the Platform Independent Model (PIM) carried out by using RT UML, and its Platform Specific Model (PSM) implemented by sub-system paradigms and object-oriented mechanisms to entirely perform the development lifecycle of quadrotor UAV controllers. The object transformation rules are also introduced and applied to convert the detailed control design model of PIM into the implementation model of PSM using open-source platforms in order to quickly simulate and realize the control performance and operational functionalities of system. Based on this approach, a trajectory-tracking controller of a mini quadrotor UAV is completely developed and successfully taken on trial flights.
Keywords: Quadrotor UAV control, Autonomous flying robots, Object-oriented analysis and design, Hybrid automata, Real-Time UML, MDA
Title of the Paper: Reduction of Residual Generated by Vibration Actuator Type Motor Step in a Flexible Beam Euller-Bernoulli
Authors: Wantuir Ap. Freitas, André Fenili, Mário César Ricci
Abstract: The technique for formatting the input shaping, based on the pole-zero cancellation is used to reduce the residual vibration in a flexible structure. The technique is developed in the discrete time domain and was extended for a step motor actuator where the motor drive commands were modified to act as passive control. The mathematical model is represented by a central body, wings of rigid solar panels and a flexible beam as shown in Figure 1. The methodology of the system analyze was developed as a multi-body problem in the Cartesian plane. The external torque, which acts on the structure, was generated by stepper motor actuators, whose step numbers were variable in order to cause an effect on the structure and minimize the linear structural response on the flexible beam. Two passive control strategies to minimize the vibration of the flexible beam first vibration mode, were investigated. The first strategy allocates a zero on the pole of the system and the second considers uncertainties on the system parameters and two zeros were placed near the pole.
Keywords: stepper motor, digital control, pole-zero, vibration, normal modes, input shapers
Issue 11, Volume 12, November 2013
Title of the Paper: Orthogonal Permutation Particle Swarm Optimizer with Switching Learning Strategy for Global Optimization
Authors: Xianghua Chu, Qiang Lu, Ben Niu
Abstract: This paper aims to improve the performance of original particle swarm optimization (PSO) so that the consequent method can be more robust and statistically sound for global optimization. A variation of PSO called the orthogonal permutation particle swarm optimization (OPPSO) is presented. An orthogonal permutation strategy, based on the orthogonal experimental design, is developed as a metabolic mechanism to enhance the diversity of the whole population, where the energetic offspring generated from the superior group will replace the inferior individuals. In addition, a switching learning strategy is introduced to exploit the particles’ historical experience and drive individuals more efficiently. Seven state-of-the-art PSO variants were adopted for comparison on fifteen benchmark functions. Experimental results and statistical analyses demonstrate a significant improvement of the proposed algorithm.
Keywords: Soft Computing, Particle swarm optimization, Orthogonal experimental design, Learning strategy, Global optimization
Title of the Paper: Formal Representation of Bulgarian Pronouns
Authors: Velislava Stoykova
Abstract: The paper presents a computationally tractable application of Bulgarian pronouns representation using Universal Networking Language (UNL) formalism. It analyses grammar features of pronouns and offers amodel of their formal representation based on incorporation of grammar, semantic and lexical knowledge by using standard UNL knowledge representation mechanisms. Also a comparison of different approaches to formal representation of Bulgarian possessive and reflexive-possessive pronouns inflectional morphology is offered. The interpretation is based on detailed analysis of grammar features and semantics of possessive and reflexive-possessive pronouns, and related formal representations are based on the use of semantic networks. The problem is interpreted as a grammar knowledge representation task.The UNL interpretation presents both morphological and syntactic knowledge and offers multilingual web-based application which can be further developed and elaborated.
Keywords: Natural Language Processing Systems, Semantic Networks, Knowledge Representation
Title of the Paper: PHIL Simulation of a Parallel HEV Equipped with Different Energy Storage Systems
Authors: Junyi Liang, Jianlong Zhang, Chengliang Yin, Futang Zhu
Abstract: Simulation has been acknowledged as an effective method of optimizing fuel consumption and sizing components for hybrid electric vehicles (HEVs). However, the accuracy of simulation results requires validation. Power-hardware-in-the-loop (PHIL) simulation can be an effective technique in obtaining accurate results and comparing different options before prototyping. Using the PHIL concept, this paper presents an implementation of a parallel HEV architecture on a dynamometer power train system. Four different energy storage systems (ESSs) in the HEV were tested to compare the performance of each system. The four ESSs included the battery-only type and the battery/ultra capacitor-based hybrid type. A fuzzy logic energy management strategy was implemented to address the power distribution in the HEV. In this paper, we compare and discuss the energy efficiency, electrical performance of the ESSs, and fuel economy of the HEV. The results show that hybrid ESSs have several advantages over the battery-only systems.
Keywords: Hardware-in-the-loop, Hybrid electric vehicle, Energy Storage System, fuzzy logic
Title of the Paper: A Type of Radial Basis Function Technique for Control and Time Series Prediction of Positioning Systems
Authors: Michail G. Papoutsidakis, Anthony G. Pipe
Abstract: It is well known that pneumatic positioning systems are still irreplaceable in many application fields like industrial automation. The maintenance cost, the low level pollution and the high speed of operation, force the use of such systems. The pneumatic piston position control has always been a challenge and engineers have applied many control methods in order to achieve position accuracy. Apart from air compressibility, the most important issue to be solved is the highly nonlinear phenomena inside the cylinder body that become unpredictable over time and long term operations of the system. Multiple friction forces, energy losses and sealing deformations are always present in this type of actuating process. In this research work, an intelligent control approach is implemented for the task, in an attempt to overcome the classical control methods inefficiency. A subcategory method of artificial neural networks is adopted for investigation, which is described in details. All experimentation results, system performance behaviour discussion and possible further improvements, form the rest of this paper body.
Keywords: Artificial Neural Networks, Nonlinear Control, Time Varying Positioning System
Title of the Paper: Convenience Yields and Arbitrage Revenues of Emission Allowances between Spot and Futures
Authors: Kai Chang
Abstract: Based on the data samples using EUA spot and futures in the ICE and BLUENEXT exchange platform in the European Union emissions trading scheme (EU ETS), this paper propose the market behavior of convenience yields and examine the options feature of convenience yields for emission allowances. When the convenience yields of emission allowances are positive, the convenience yields are positively related with the spread between spot expected value and futures price of emission allowances. When the convenience yields of emission allowances are negative, the absolute value of convenience yields are positively related with the spread between futures price and spot expected value of emissions allowances, and then the convenience yields of emission allowance have a significant options property. Our empirical evidence show that when the convenience yields are call or put options, market participants can flexibly adjust portfolio policies of emission allowances assets, based on the extension of options pricing model of assets exchange, and then achieve extra market arbitrage revenues through exchanging emission allowances assets between spot and futures.
Keywords: emission allowances, convenience yields, options property, assets exchange, arbitrage revenue
Title of the Paper: Quantifying the Value of Subjective and Objective Speech Intelligibility Assessment in Forensic Applications
Authors: Giovanni Costantini, Andrea Paoloni, Massimiliano Todisco
Abstract: Transcription from lawful interception is an important branch of forensic phonetics. Signals in that application context are often degraded, thus the transcript may not reflect what was really pronounced. In order to decide whether a given transcript generated from a lawful interception exercise reflects the views of the speakers instead of the transcriber’s, an objective speech intelligibility measurement method is required. Usually, the intercepted signal can be affected by both speech intrinsic distortion and background/environmental noise distortion. Unfortunately, the original clean speech is never accessible to the forensic expert, who therefore must draw his assessment from the only available, distorted, signal. Consequently, the only way to assess the level of accuracy that can be obtained in the transcription of poor recordings is to develop an objective methodology for intelligibility measurements. This paper addresses the issue by using three different objective approaches - namely the Signal-to-Noise ratio weighted with the “A” curves (S/NA), the Articulation Index (AI) and the Speech Transmission Index (STI) - to evaluate the intelligibility of a given signal. All of the three approaches were exercised with different types of noise, yielding results to be compared with speech intelligibility scores from subjective tests. The outcome gives high correlation evidence between objective measurements and subjective evaluations. Therefore, the proposed methodology is deemed rather useful to establish whether a given intercepted signal can be transcribed with sufficient reliability.
Keywords: Objective intelligibility, forensic phonetics, speech transmission index, transcript reliability
Title of the Paper: Research on Generating Step Value Algorithm for Gray Level Cooccurrence Matrix and Its Application in Tool Monitoring
Authors: Lihong Li, Qingbin An, Minglu Zhang, Jianhua Zhang
Abstract: The monitoring of tool wear condition can be processed by means of the analysis of workpiece surface texture images. In order to analyze the workpiece surface texture images accurately, the generating step value of Gray Level Co-occurrence Matrix is studied extensively. A new algorithm about generating step value is proposed in this paper. Through analysis and testified by experiments, the optimum value of the generating step value is the step value which makes the textural feature parameters obtain the extreme value(the maximum or minimum value) in the first period. The optimum value of the generating step value is only related with the feed rate. It is unrelated with the other machining parameters such as the tool wear and machining speed. Compared with the other step value, the optimum value of the generating step value makes GLCM more different and diverse for different texture images. Therefore the difference of textural feature parameter values based on the above GLCM is great. Consequently the feature parameters obtained by the reasonable generating step value are sensitive to the tool wear which are beneficial to monitor the tool wear.
Keywords: Image processing, Texture analysis, Tool wear monitoring, Gray Level Co-occurrence Matrix, Generating step value, Feature parameters
Title of the Paper: On the Measurement of Wave Propagation in Systems by Means of Spherical Microphone Array: A Case Study
Authors: Lamberto Tronchin
Abstract: The measurements of wave propagation in linear and non-systems represent an important research topic. The study of wave propagation becomes very important especially when related with sound propagation in enclosures, as pipes, theatres, and other electro-acoustic systems, that are normally considered non linear. In this article, a new method for recording the spatial properties of the wave propagation is described. The spatial distribution of air-pressure waves passing at a point in space is sampled by means of a number of virtual directive microphones, covering the surface of a sphere. This represents a discretization of the spatial information, which corresponds to the spatial equivalent of the PCM sampling of a waveform. In this article the measurements of air-pressure wave propagation in enclosures is analysed starting from a traditional b-format microphone, and compared with a 32-channels probe. The method is applied to a historical Italian theatre, located in Bologna, i.e. the 1763 theatre in Villa Mazzacorati. In order to properly evaluate the early components of the multichannel Impulse Response, a panoramic picture of the theatre was considered. On this picture, the early reflections were plotted into different circles on the figure, where the dimension and the intensity are related with the characteristics of the early components. Furthermore, also the influence of the height of the microphone in the calculation of the physical parameters was analysed. The measurements were repeated at different height and different position on a transversal line in the theatre, and statistically analysed.
Keywords: Wave propagation in systems, Spherical array probe, 3D Impulse Responses, Uncertainty, linear and non linear systems
Issue 12, Volume 12, December 2013
Title of the Paper: The Effect of Stock Market Mispricing on Investment — Evidence from China
Authors: Su-Sheng Wang, Fang Zhao, Dong-Feng Wang
Abstract: Using a large panel of Chinese listed firms, we introduce market timing theory and investigate if mispricing in the stock market has an impact on firm-level investment. The article discusses the relationship between equity mispricing and equity dependence. A significantly positive relation is documented between investment and the proxies for mispricing, suggesting that overpriced (underpriced) firms tend to overinvest (under-invest).Furthermore, we find that based on financing constrains index equity-dependent firms which display a more pronounced sensitivity of investment to stock misevaluation than do non-equity-dependent firms. Our findings show that mispricing in Chinese capital markets may have significant influence on the real economy, and the influence works though an equity-financing channel.
Keywords: Investment-Q, Equity dependence, Investment, Chinese listed firms
Title of the Paper: Automatic Parameter Calibration for Frequency Modulated Sound Synthesis with a Faster Differential Evolution
Authors: Sohan Ghorai, Sumit Kumar Pal
Abstract: Frequency Modulated sound synthesis is a technique widely used for replicating sound of a natural music instruments to use it in a computer sound synthesizer. Many sound synthesis technique have been successful in reproducing the sounds of musical instruments. Sound synthesis techniques require parameter calibration. However, this task can be difficult and time consuming because of the non-linear parameter space. Two difficult challenges have to handle for synthesizing sound, that is-proper parameter extraction from a difficult search space and search time, which matters for a real time application. This article presents an application of stagnation adaptive DE scheme for faster parameter identification of a FM synthesized sound to match an unknown target sound. The simulation result shows that DE can perfectly reproduce the sound signal over other algorithm and also have a very faster convergence rate than classic DE.
Keywords: differential evolution, sound synthesis, frequency modulation, optimization, parameter identification
Title of the Paper: A New Method for Crankpin Bearing Fault Diagnosis Based on Dynamic Pressure Simulation and Condition Monitoring
Authors: Jinjie Zhang, Zhinong Jiang, Yinan Xie, Na Lu
Abstract: Connecting rod is a crucial part of the reciprocating compressor and the crankpin bearing fault of connecting rod is always the obstacle in fault diagnosis. Normally the condition monitoring of connecting rod and dynamic analysis are based on cylinder dynamic pressure monitoring which is also an important method for fault diagnosis. However, it is hard to diagnose crankpin bearing fault in realistic when it comes to the reciprocating compressor unfit for installing pressure transducers because there is no indicator hole or the pressure is too high. In this paper, a new method is presented to deal with above problems. The theoretical three-dimensional models of cylinder and valves of the experiment platform are established to finish the numerical simulation of dynamic pressure which has been compared with the actual measured dynamic pressure signals. Dynamic analysis of crankpin bearing with actual fault is applied to find out the abnormal impact phases. Contrasting results show that actual vibration impact phases are consistent with those of theoretical calculation. The realistic fault maintenance finally confirms the effectiveness of the new method.
Keywords: Connecting rod, Reciprocating compressor, Crankpin bearing, Numerical simulation, Dynamics analysis
Title of the Paper: A Data Envelopment Analysis Evaluation and Financial Resources Reallocation for Brazilian Olympic Sports
Authors: Renato Pescarini Valério, Lidia Angulo-Meza
Abstract: This paper proposes the use of a Data Envelopment Analysis model to evaluate the Brazilian Olympic sports efficiency and also to reallocate the financial resources received by them. The sports selected were those that received financial resources from the Agnelo/Piva Law in 2011. As proposed in previous works, we use as inputs the funds received and medals offered, as a proxy for difficulty measure in winning a medal; and the results obtained (gold, silver and bronze medal) as outputs. We proposed to use the results from the Pan-American Games, specifically from the 2011 Pan-American Games, since we believe that the Olympic Games results were scarce to assess the sports efficiency as there are many null results for lots of sports. Therefore, the medals related to the 2011 Pan American Games are used in this paper. A DEA non-radial model with weights restrictions is formulated to perform the Olympic sports efficiency evaluation. With these results a financial resources reallocation is proposed using a ZSG-DEA non-radial approach. Results show that using data with minimal null medals leads to a good financial resources reallocation, based on the sports efficiency, without the need of including anymore variables or imposing additional weight restrictions.
Keywords: Data Envelopment Analysis, Olympic sports, sports efficiency, financial resources reallocation
Title of the Paper: The Effects of Ownership and Capital Structure on Environmental Information Disclosure: Empirical Evidence from Chinese Listed Electric Firms
Authors: Kai Chang
Abstract: Based on 2006 sustainability reporting guidelines and environmental information disclosure measurement issued by the Global Reporting Initiative (GRI), this paper proposes a quantitative estimation of ownership structure, capital structure and environmental information disclosure (EID) for 25 listed firms in Chinese electric industry, presents the empirical evidence of the effects of ownership and capital structure on environmental information disclosure. Our empirical results show that state legal-person ownership, non-state ownership, ownership concentration, financial leverage, long-term debts and short-term debts have significantly positive impacts on environmental information disclosure. Compared with listed electric firms who own higher non-state ownership, listed firms owned higher state ownership tend to disclose more environmental information in an active and voluntary behavior. Listed firms with an increase of ownership concentration and financial leverage voluntarily disclose more environmental information, which is helpful for stakeholders to reducing environmental and financial risk. Compared with short-term debt, long-term debt have a significant effect on EID, listed firms owned greater long-term debts tend to disclose more environmental information, it is helpful for creditors to decreasing financial and environmental risks. Finally we propose a series of policies and advices such as strengthening the control capacity of state-owned assets, strictly carrying out environmental regulation policies, improving ownership and capital structure, and providing capital market and green financing policies etc.
Keywords: ownership structure, ownership concentration, capital structure, environmental information disclosure, listed electric firms
Title of the Paper: Lean Maintenance Model to Reduce Scraps and WIP in Manufacturing System: Case Study in Power Cables Factory
Authors: Elpidio Romano, Teresa Murino, Felice Asta, Piervincenzo Costagliola
Abstract: The aim of this paper is to develop an innovative Lean Maintenance model in order to optimize the process flow and reduce or eliminate scraps and work-in-progress (WIP) in a manufacturing context. To achieve these objectives has been formulated a new method, called Lean Root Cause & Defect Analysis (LRCDA), which merges the process steps of the existing Root Cause & Failure Analysis (RCFA) technique and basic principles of Lean Maintenance and Total Productive Maintenance (TPM).The LRCDA is a logical sequence of phases the leads the investigator through the process of isolating the facts surrounding the event or the fault. After the problem defining, the analysis determines the best actions, corrective and preventive, to will resolve the problem and its recurrence. The model has been implemented for the first time in a power cables factory with intent to reduce the partial discharges phenomena in medium voltage (MV) cables.
Keywords: lean maintenance, total productive maintenance, maintenance-production relationship, autonomous maintenance, root cause, failure analysis
Title of the Paper: Intelligence Diagnosis Method Based on Particle Swarm Optimized Neural Network for Roller Bearings
Authors: Zuoyi Dong, Huaqing Wang, Shuming Wang, Wei Hou, Qingliang Zhao
Abstract: This paper presents an intelligent diagnosis approach based on the particle swarm optimized BP (PSO-BP) neural network and the rough sets to detect roller bearings faults and distinguish fault types, using symptom parameters of acoustic emission signals. The rough sets algorithm is used to reduce details of time-domain symptom parameters for the training of the neural network instead of principal component analysis. The PSO-BP neural network, which used for condition diagnosis of roller bearing, can obtain good convergence using the symptom parameters acquired by the rough sets when learning, and can automatically distinguish fault types when diagnosing. Using the PSO-BP neural network can increase the learning rate and the subtracting capability of the neural network. Practical examples are provided to verify the efficiency of the proposed method.
Keywords: Intelligence diagnosis, Particle Swarm Optimization, BP neural network, PCA, Rough set, Fault Diagnosis, Roller Bearings
Title of the Paper: VHDL Modeling of Booth Radix-4 Floating Point Multiplier for VLSI Designer’s Library
Authors: Wai-Leong Pang, Kah-Yoong Chan, Sew-Kin Wong, Choon-Siang Tan
Abstract: Floating point arithmetic computation has been widely used today in graphics, digital signal processing, image processing and other applications. Multiplication is the most complex calculation that used in most digital electronic circuit. The multiplier may have large chip area density, high complexity, and is a time consuming computation because the output data size is twice larger than input data size. Complex floating point multiplication required more time to process data and is highly recommended to improve the computation speed. The performance in terms of computation and processing speed is one of the major factors in today’s Very/Ultra Large Scale Integration (VLSI/ULSI) system design. The objective of this research is to design a 32-bit floating point multiplier for Very high speed integrated circuit Hardware Description Language (VHDL) designer’s library that consists of mantissas multiplier, normalizer, exponent adder, and signer for VHDL designer’s library that lack of floating point multiplier module. Booth radix-4 algorithm is used in the multiplier, mainly due to the simplicity of this algorithm to be modeled using VHDL and at the same time it provides good performance. The 32-bit floating point multiplier is tested on Arria II GX chip to determine their performance in terms of slack, maximum frequency and minimum clock period by using TimeQuest Timing Analyzer. Booth radix-4 multiplier in Arria II GX (EP2AGX45CU17I3) produces a maximum frequency of 206.14 MHz and minimum allowed clock period of 5 ns. Benchmarking has been carried out between the Booth radix-4 and Wallace Tree multipliers, since Wallace Tree multiplier can provide better performance to the VLSI system design. The resource consumption of Booth radix-4 multiplier is 88.8% less than the Wallace Tree multiplier and the performance of Booth radix-4 multiplier is almost equal to the Wallace Tree multiplier.
Keywords: VHDL, Booth Radix-4, Floating Point Multiplier