Optimization of Fuzzy Sliding Mode Controller with Improved Genetic Algorithm

Sliding mode controller (SMC) is widely used in the field of motor control systems, but its discontinuous switching characteristics would cause system chattering. To reduce the inherent chattering, a new adaptive fuzzy sliding mode control (AFSMC) strategy is proposed in this paper. The fuzzy terms are introduced in the sliding mode controller and optimized by using improved genetic algorithm. The simulation results demonstrate that the new controller has higher response speed and lower chattering than traditional sliding mode controllers. The controller can increase the precision of the permanent magnet linear synchronous motors (PMLSM) direct-driven servo control systems.