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The controller\r\ndetermines the optimal control law for the process using the estimates it\r\nreceives. An attacker aims at degrading the control performance by increasing\r\nthe packet-dropout rate with a DoS attack towards the sensor-controller\r\nchannel. We assume both the controller and the attacker are rational in a\r\ngame-theoretic sense and establish a partially observable stochastic game to\r\nderive the optimal joint design of scheduling and control. Using dynamic\r\nprogramming we prove that the control and scheduling policies can be designed\r\nseparately without sacrificing optimality, making the problem equivalent to a\r\ncomplete information game. We employ Nash Q-learning to solve the problem and\r\nprove that the solution is guaranteed to constitute an $\\epsilon$-Nash\r\nequilibrium. Numerical examples are provided to illustrate the tradeoffs\r\nbetween control performance and communication cost.","lang":"eng"}],"author":[{"last_name":"Lu","full_name":"Lu, Jingyi","first_name":"Jingyi"},{"first_name":"Daniel E.","last_name":"Quevedo","full_name":"Quevedo, Daniel E."}],"date_created":"2023-01-09T16:48:44Z","date_updated":"2023-01-09T18:04:57Z","title":"A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks","citation":{"ama":"Lu J, Quevedo DE. A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks. <i>arXiv:210305893</i>. Published online 2021.","chicago":"Lu, Jingyi, and Daniel E. Quevedo. “A Jointly Optimal Design of Control and Scheduling in Networked Systems  under Denial-of-Service Attacks.” <i>ArXiv:2103.05893</i>, 2021.","ieee":"J. Lu and D. E. 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