A novel adaptive fuzzy generalized predictive control for a class of nonlinear systems

A novel adaptive fuzzy generalized predictive control scheme is presented for a class of nonlinear systems. The unknown nonlinear plants are represented by an equivalent model composed of a simple linear submodel plus a nonlinear submodel around operating points. A linear generalized predictive controller is designed based on the linear submodel, a compensation term, which is implemented with a adaptive fuzzy system, is introduced to control nonlinear systems, the unknown parameters adaptation law is derived from Lyapunov stability theory. The proposed design scheme guarantees that all the signals in the resulting closed-loop system are bounded, and the response of the proposed schemes of this paper can almost agree with that of the linearized system. Simulation results indicate the effectiveness of this scheme.