Adaptive Decentralized Output Feedback Tracking Control for Large-Scale Interconnected Systems with Time-Varying Output Constraints

Abstract

This paper investigates a novel adaptive output feedback decentralized control scheme for nonstrict feedback large-scale interconnected systems with time-varying constraints. A decentralized linear state observer is designed to estimate the unmeasurable states of subsystems. Time-varying barrier Lyapunov functions are designed to ensure outputs are not violating constraints. A variable separation approach is applied to deal with the nonstrict feedback problem. Moreover, dynamic surface control and minimal parameter learning technologies are adopted to reduce the computation burden, and there are only two parameters for every subsystem to be updated online. The proof of stability is obtained by the Lyapunov method. Finally, simulation results are given to show the effectiveness of the proposed control scheme.