In this paper, fuzzy sliding mode controller based on genetic algorithms is designed to govern the dynamics of rigid robot manipulators. When fuzzy sliding mode control is designed there is no criterion to reach an optimal design. Therefore, we will 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 sliding 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 that.
展开▼
