Bald eagle search-based model-free fast super-twisting sliding mode control for linear induction motors

Abstract

To address the issue of degraded control performance in linear induction motor (LIM) systems caused by nonlinearities and uncertainties, this paper proposes a model-free adaptive fast super-twisting sliding mode control strategy (BES-MFAFSTSMC), in which controller parameters are optimized using the Bald Eagle Search (BES) algorithm. First, a Partial Form Dynamic Linearization (PFDL) data model is established based on the input–output data of the LIM system. Then, using this data model, a controller is designed by integrating a discrete terminal sliding mode function and a discrete fast super-twisting reaching law. To ensure control quality, an exponential decay term is introduced into the sliding surface to accelerate error convergence, while a discrete cumulative term is incorporated into the reaching law to effectively reduce system chattering and enhance robustness. The controller parameters are optimized using the BES algorithm. Finally, the Lyapunov stability theory is employed to prove the stability of the proposed control strategy. Simulation results demonstrate that the proposed method effectively improves the dynamic performance and robustness of the LIM system.