Observer based Fuzzy Integral Model Predictive Control using Piecewise Lyapunov Functions

Abstract

In this paper, a novel stable observer-based integral model predictive controller using piecewise Lyapunov functions is proposed for constrained nonlinear systems. The main idea is to design integrator based state feedback control laws that minimize the worst-case objective function based on fuzzy model prediction, and then to design observer based output feedback controller. It is expected that satisfactory transient control performance without any steady-state offset can be achieved. The asymptotic stability of the resulting closed-loop predictive control system is established by solving a set of linear matrix inequalities. Simulations on a highly nonlinear benchmark system are finally presented to demonstrate the tracking performance of the proposed output feedback fuzzy predictive controllers.