Tracking Control Based on Improved Fuzzy Gauss Radial Basis Function Neural Network for Omni-Directional Intelligent Wheelchair

Abstract

In conventional fuzzy neural network based on sigmoid function, the number of nodes at the corresponding intermediate layer grows larger with the increase of fuzzy rule numbers. In order to obtain real time performance of the control system, an improved fuzzy Gaussian radial basis function neural network controller for omni-directional intelligent wheelchair was proposed. The structure and the design method of the improved controller were described in detail. The optimized fuzzy neural network reduced the numbers of intermediate lay, thus the computation real time ability could be guaranteed. Furthermore, the stability of the controller was proved through Lyapunov stability theory. Finally, the proposed optimized controller was applied to an omni-directional intelligent wheelchair, and the simulation results of tracking control verified the real time, effectiveness and feasibility of the proposed method.