文摘
Soft-computing based control is fast emerging as the method of implementation of intelligent automation in real world systems. Not only industrial systems, but a wide range of other diagnostic, predictive and autonomous control systems rely on soft computing tools, particularly on fuzzy logic, for the design of intelligent control system. This paper presents the design and application of a fuzzy sliding mode controller for dynamic nonlinear systems. The Takagi-Sugeno (T-S) fuzzy model has been used to represent the nonlinear system and design the fuzzy controller. The Parallel Distributed Compensation (PDC) has been used with sliding mode control to design the controller, with an aim to improve the performance of the system by output tracking with disturbance rejection. The proposed controller is better than the conventional PDC based fuzzy controller and has better output tracking efficiency robustness. The proposed methodology has been successfully employed for the well-established benchmark nonlinear system, viz., inverted pendulum on cart. Simulation results show that the designed fuzzy sliding mode controller tracks the desired output trajectory very fast, while rejecting disturbances.
