Observer-Based Adaptive Fuzzy Decentralized Control of Uncertain Large-Scale Nonlinear Systems with Full State Constraints

Abstract

In this paper, the problem of observer-based adaptive fuzzy decentralized control is studied for uncertain large-scale nonlinear systems with full state constraints, input saturation and unmeasurable state. Compared with the existing literature, the state directly measurable problem is relaxed, and the systems with full state constraints and input saturation problem are further considered. In order to solve the controller design difficulties caused by input saturation and state constraints, the auxiliary design functions and the barrier Lyapunov functions are employed, respectively. By utilizing adaptive backstepping technique and Lyapunov stability theorem, an observer-based adaptive fuzzy decentralized control approach is developed. It is proved that all the signals of the closed-loop systems are semi-globally uniformly ultimately bounded and the observer errors are converged on a small neighborhood of the origin. The tracking errors are remained in the bounded compact set, and the full state constraints are not violated. Two practical examples are given to demonstrate the usefulness of the proposed control scheme.