Fuzzy model reference adaptive control design for uncertain nonlinear time-delay systems

In this paper, the problem of fuzzy model reference adaptive control (FMRAC) for a class of continuous-time multiple-input-multiple-output (MIMO) nonlinear uncertain systems with state delays and external disturbances is investigated. A reference model with the desired amplitude and phase properties is given to construct an error model. A fuzzy system is used to approximate an unknown optimal control law from the strategic manipulation of the model following tracking errors. The proposed FMRAC scheme uses on-line estimations for the control gains. Based on the Lyapunov stability theorem, a fuzzy adaptive control strategy using Takagi-Seguno (TS) fuzzy system with proportional-integral (PI) type can guarantee parameter estimation convergence and stability robustness of the closed-loop system. The performance of the proposed scheme is evaluated through the simulation results. A 2 DOF parallel robot control problem is simulated to demonstrate the validity of the proposed scheme.