文献类型：期刊文献

英文题名：Resilient Optimal Output Regulation under Denial-of-Service Attacks with an Application to Autonomous Vehicles

作者：Dong, Yuchen[1]; Gao, Weinan[1]; Li, Zhongmei[2]

机构：[1] Northeastern University, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China; [2] East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, Shanghai, China

年份：2025

起止页码：2370

外文期刊名：IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

收录：EI(收录号：20261820605861)

语种：英文

外文关键词：Adaptive control systems - Behavioral research - Closed loop systems - Cognitive systems - Computation theory - Control theory - Dynamic programming - Gradient methods - Input output programs - Linear systems - Optimal control systems - System stability

摘要：In this paper, a novel resilient optimal control framework is proposed for linear systems under denial-of-service attacks. By integrating adaptive dynamic programming, the gradient descent method, and the output regulation theory, the resilient optimal controller can be learned directly from the real-time state and input data of the attacked system. In addition, a sufficient condition for the stability and resilience of the closed-loop system under denial-of-service attacks is provided. Finally, the effectiveness of the proposed resilient control algorithm is verified by simulation of autonomous vehicles. ? 2025 IEEE.