A Novel Robust Adaptive-Fuzzy-Tracking Control for a Class of Nonlinear Multi-Input/Multi-Output Systems

Robust adaptive-fuzzy-tracking control of a class of uncertain multi-input/multi-output nonlinear systems with coupled interconnections is considered in this paper. Takagi-Sugeno (T-S) fuzzy systems are used to approximate the unknown system functions. A novel adaptive-control scheme is developed on the basis of the so-called dynamic-surface control and minimal-learning parameters techniques. The proposed scheme has following two key features. First, the number of parameters updated online for each subsystem is reduced to one, and both problems of curse of dimension for high-dimensional systems and explosion of complexity inherent in the conventional backstepping methods are circumvented. Second, the potential controller-singularity problem in some of the existing adaptive-control schemes with feedback-linearization techniques is overcome. It is shown via Lyapunov theory that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, simulation results via two examples are presented to demonstrate the effectiveness and advantages of the proposed scheme.