Quantized stabilization of switched systems with partly unstabilizable subsystems and denial‐of‐service attacks

Abstract

This article addresses the problem of stabilizing a continuous-time switched system affected by quantization and denial-of-service (DoS) attacks. The switching is assumed to be slow enough in the sense of combined dwell time and average dwell time, individual modes are assumed to be partly unstabilizable, and DoS attacks are supposed as energy limited by restraining DoS frequency and DoS duration. By introducing a Decision Maker into the system framework and proposing a switching algorithm for the attacked intervals, we simplify the design rules of the controller and divide the system status into four cases.On the basis of approximating the reachable set and analyzing the increasing/decreasing rate of Lyapunov function for each case, the sufficient conditions ensuring the exponential convergence and Lyapunov stability of the closed-loop system are obtained. Two examples are illustrated to demonstrate the effectiveness of the theoretical analysis.

Resilient control for networked control systems with dynamic quantization and DoS attacks

“…In the work of Wu et al, 29 the quantizer adjusts quantization intervals based on the amplitude of system states, while it follows from (8) that the update rule of the quantizer we designed only depends on the time instants of successful transmission. Although continuous‐time systems were considered in the work of Yan et al 30 and Kato et al, 31 the quantization intervals are govern by discrete‐time iterations. However, a novel continuous‐time update strategy of quantization intervals is designed for continuous‐time systems in this article.…”

“…Although continuous-time systems were considered in the work of Yan et al 30 and Kato et al, 31 the quantization intervals are govern by discrete-time iterations. However, a novel continuous-time update strategy of quantization intervals is designed for continuous-time systems in this article.…”

“…Inspired by the technique of the zooming-in and zooming-out, we design a novel dynamic quantization strategy, in which the quantization step sizes are time-varying. Different from the existing dynamic quantization strategies, 23,[28][29][30][31] in our design, the quantizer is with its own dynamics and the update rule of the quantizer only depends on the time instants of successful transmission. The quantization errors converge to zero under the designed quantization strategy when states approach the origin.…”

“…The designed quantization strategy is with time-varying step sizes, which can dynamically force quantization errors to decay to zero. Compared with the existing dynamic quantization strategies, 23,[28][29][30][31] the quantizer designed in this article is with continuous-time dynamics and the update rule of the quantizer we designed only depends on the time instants of successful transmission. Moreover, an…”