Nonlinear model reference adaptive control using Takagi-Sugeno fuzzy systems

This paper develops a new direct model reference fuzzy adaptive control of SISO continuous-time nonlinear systems. The model following conditions are assured by using an adaptive Takagi-Sugeno (TS) fuzzy system as nonlinear state feedback controller. Both full state information and observer-based control schemes are investigated. It is shown, that the proposed control algorithm guarantees the stability of the nonlinear system with the tracking and state estimation errors converging to the neighborhood of the origin for all realizations of uncertainties and disturbances. Compared to previous works this approach is much simpler and less assumptions are required. Simulation results for controlling inverted pendulum system are given.