Abstract: Magnetic levitation systems are nonlinear and open-loop unstable, which makes accurate and robust control difficult. This paper investigates two sliding-mode-based controllers for a nonlinear MagLev system: the Super-Twisting Sliding Mode Controller (STSMC) and a Conditioned Barrier Adaptive Function Double-Integral Terminal Super-Twisting Sliding Mode Controller (CB-STSMC). Both controllers are designed to regulate the levitation gap while ensuring proper tracking of magnetic flux and momentum states. Their gains are optimized using a Genetic Algorithm with the Integral of Time-weighted Absolute Error as the fitness criterion. Closed-loop stability is established through Lyapunov analysis. MATLAB/Simulink results show that both controllers achieve stable levitation, while the proposed CB-STSMC provides faster convergence, smaller overshoot, and improved disturbance rejection compared with the conventional STSMC. These results confirm the effectiveness of the proposed strategy for robust and precise nonlinear MagLev control.

Keywords: Magnetic levitation, Super-Twisting Sliding Mode Control, Conditioned Barrier Adaptive Function, Terminal Sliding Mode Control, Genetic algorithm optimization, advanced sliding Mode controllers

Pages: 103-111