Observer-based adaptive fuzzy containment control for state-constrained nonlinear MASs based on quantization communication

Abstract

In this article, the fuzzy adaptive output feedback quantized containment control problem is investigated for state-constrained nonlinear multi-agent systems (MASs). The state observer and FLSs are utilized to obtain the state estimations and approximate the unknown nonlinear dynamics, respectively. An estimation is designed to model the unknown local reference signal caused by the unavailability of the global information. To solve the nondifferential problem of the virtual controllers caused by the quantized outputs of neighbors, an auxiliary system is designed, under which the noncontinuous filter errors can be replaced by the auxiliary signals. By introducing the log-type barrier Lyapunov function (BLF) to backstepping recursive design, an adaptive fuzzy quantized containment controller is developed. Based on the Lyapunov stability theory, it is proved that the closed-loop system is stable, the output of each follower can be driven into the dynamic convex hull spanned by the leaders, and the states of system will not exceed their constrained bounds. Finally, a group of two virtual leaders and three unmanned surface vehicles (USVs) are utilized to test the effectiveness of the developed control approach.