AI-based discrete sliding-mode control for real-time implementation

Combination of sliding-mode control and an AI block based on fuzzy logic is introduced. This hybrid control structure provides very good control performance and robustness of control loops. Based on the Lyapunov’s direct method, the sliding mode control is designed to guarantee the stability and good tracking performance of controlled systems. The fuzzy logic block is designed to mimic the behavior of a vehicle driver who attempts to maintain a constant speed while travelling on a road with ascending and descending sections. The fuzzy logic block acts as a dumper on the system transients and enhances the robustness of the control loop. The control algorithm is developed for implementation in demanding real-time control applications. The new controller is compared via simulation experiments to the optimally tuned PI controller and the pure sliding mode controller. It shows the best performance of all three compared controllers. These Þndings were corroborated in the real-time speed control experiments with the induction motor test-bed system.