Decentralized Output Feedback Control for Interconnected Nonlinear Systems Under Network Constraints via a Dynamic Gain Design Approach.

Abstract

This article investigates decentralized event-triggered dynamic output feedback adaptive fuzzy control for interconnected nonlinear systems under injection attacks and input quantization. Different from previous works, we propose a reduced-order dynamic observer-based event-triggered quantized control method under a relaxed Lipschitz condition and output injection attack, which effectively reduces computational burden and communication resource usage. First, a novel reduced-order dynamic gain observer estimates unmeasured states under injection attacks. Subsequently, to guarantee that each subsystem's output satisfies the prescribed performance requirements, a barrier-function-based tracking error mapping approach is proposed. Then, an adaptive fuzzy control scheme incorporating decentralized event-triggered output feedback and input quantization is developed using the backstepping technique, thereby optimizing energy efficiency in signal transmission. Next, Lyapunov analysis proves that all closed-loop signals remain bounded with Zeno behavior excluded. Finally, simulations validate the theoretical results under various attack scenarios.