Fuzzy controller design under imperfect premise matching for discrete-time inverted pendulum robot systems

Abstract

This paper presents the fuzzy controller design using Imperfect Premise Matching (IPM) for inverted pendulum robot system. With the movable supportive base, the inverted pendulum robot system can be applied to simulate human stance. Moreover, the Takagi-Sugeno (T-S) fuzzy model is employed to describe the complex nonlinearities of the system. And, the multiplicative noise term is introduced in the consequent part of fuzzy system to present the stochastic behavior of system. In order to extend the application of this paper, the IPM technique provides a generalization approach in designing proposed fuzzy controller. Based on the IPM, the fuzzy controller design can be enhanced more flexibility and robustness than one applies Parallel Distributed Compensation (PDC) approach. Finally, simulation results are given to demonstrate the usefulness and applicability of the proposed fuzzy controller design approach.