Supervised Adaptive PID Control of Unknown Nonlinear Systems Using Fuzzily Blended Time-Varying Canonical Model

This paper proposes a supervised PID adaptive control scheme for unknown nonlinear systems to enhance system robustness in the face of external disturbances, variation in system parameters, and parameter drift in the adaptation law. The supervising controller is designed based on an on-line identified model in a fuzzily blended time-varying canonical form. The model largely simplifies the identification of the nonlinear plant, and the design of both the supervising controller and the adaptation law. Numerical studies of the tracking control of an uncertain Duffing-Holmes system demonstrate the effectiveness of the proposed control strategy.