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arXiv 2103.05893eess.SYcs.SY
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拒绝服务攻击下网络系统控制与调度的联合优化设计

A Jointly Optimal Design of Control and Scheduling in Networked Systems under Denial-of-Service Attacks

Jingyi Lu, Daniel E. Quevedo

摘要:

本文研究了网络控制系统在随机拒绝服务(DoS)攻击下的控制与调度联合设计问题。传感器对系统输出进行测量,并通过分组丢弃链路将其动态状态估计转发给远程控制器。控制器使用它接收的估计来确定过程的最优控制律。攻击者的目标是通过对传感器-控制器通道进行拒绝服务攻击来增加数据包丢失率,从而降低控制性能。我们假设控制者和攻击者在博弈论意义上都是理性的,并建立了一个部分可观测的随机博弈来推导调度和控制的最优联合设计。使用动态规划,我们证明了控制和调度策略可以单独设计,而不牺牲最优性,使问题相当于一个完整的信息博弈。我们采用纳什Q学习来解决这个问题,并证明了解决方案是保证构成一个$ε$ -纳什均衡。数值例子来说明控制性能和通信成本之间的权衡。

英文摘要:

We consider the joint design of control and scheduling under stochastic Denial-of-Service (DoS) attacks in the context of networked control systems. A sensor takes measurements of the system output and forwards its dynamic state estimates to a remote controller over a packet-dropping link. The controller determines the optimal control law for the process using the estimates it receives. An attacker aims at degrading the control performance by increasing the packet-dropout rate with a DoS attack towards the sensor-controller channel. We assume both the controller and the attacker are rational in a game-theoretic sense and establish a partially observable stochastic game to derive the optimal joint design of scheduling and control. Using dynamic programming we prove that the control and scheduling policies can be designed separately without sacrificing optimality, making the problem equivalent to a complete information game. We employ Nash Q-learning to solve the problem and prove that the solution is guaranteed to constitute an $ε$-Nash equilibrium. Numerical examples are provided to illustrate the tradeoffs between control performance and communication cost.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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