Enhanced Guaranteed‐Cost H∞$$ {H}_{\infty } $$ Control for Networked Control Systems Under DoS Attacks and Actuator Saturation Using Dynamic Memory‐Based Event Triggering

This article addresses the stabilization problem of networked control systems (NCSs) under non‐periodic denial‐of‐service (DoS) attacks and actuator saturation. A non‐periodic DoS attack model is put forward, taking into account the minimum communication security time period, the maximum attack dura...

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Bibliographic Details
Published in:	International journal of robust and nonlinear control
Main Authors:	Chen, Menghua, Wang, Shuting, Reza Karimi, Hamid, Wang, Xinping, Wang, Yunming
Format:	Journal Article
Language:	English
Published:	21.08.2025
ISSN:	1049-8923, 1099-1239
Online Access:	Get full text
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Summary:	This article addresses the stabilization problem of networked control systems (NCSs) under non‐periodic denial‐of‐service (DoS) attacks and actuator saturation. A non‐periodic DoS attack model is put forward, taking into account the minimum communication security time period, the maximum attack duration, and the frequency constraint. This model facilitates the analysis of system performance in relation to attack characteristics by establishing connections between two generalized assumption models. For the NCSs suffering from both non‐periodic DoS attacks and actuator saturation, a dynamic memory‐based event‐triggered mechanism (DMETM) is designed to maintain control performance and reduce network resource consumption. To deal with the actuator saturation phenomenon, a set of memory‐based primary‐auxiliary controllers is designed to compensate for actuator saturation effects via convex hull representation. A guaranteed‐cost function accounting for system states and input saturation is developed. Based on the obtained switched system model and the piecewise Lyapunov‐Krasovskii functional (LKF), sufficient conditions are derived to ensure local asymptotic stability and weighted disturbance attenuation with performance. The co‐design of DMETM weighting matrices and controller gains is presented in the form of linear matrix inequalities (LMIs). Additionally, methods for estimating the attraction domain and deriving the upper bound of the cost function are given by the obtained LMIs. Finally, the effectiveness and superiority of the proposed method are validated on a high‐speed train system.
ISSN:	1049-8923 1099-1239
DOI:	10.1002/rnc.70161