Application of fuzzy sliding mode based on genetic algorithms to control of robotic manipulators

The paper presents the design of fuzzy sliding mode control based on genetic algorithms. An optimal design criterion is not required in the design of a fuzzy sliding mode control. Therefore, we design a fuzzy sliding mode controller for the general nonlinear control systems as an optimization problem and apply the optimal searching algorithms and genetic algorithms to find the optimal rules and membership functions of the controller. The proposed approach has the merit to determine the optimal structure and the inference rules of fuzzy siding mode controller simultaneously. Using the proposed approach, the tracking problem of two-degree-of-freedom rigid robot manipulator is studied. Simulation results of the close-loop system with the proposed controller based on genetic algorithms show the effectiveness of the approach.