Wang Lanxin, Long Yue, Li Tieshan, Park Ju H
IEEE Trans Cybern. 2024 Dec;54(12):7489-7500. doi: 10.1109/TCYB.2024.3430468. Epub 2024 Nov 27.
The model predictive control (MPC)-based asynchronous attack tolerant control scheme is investigated in this article for uncertain Markov jump cyber-physical systems (MJCPSs) under the Denial-of-Service (DoS) attack. To tackle the problem of the system running mode may not be observed in the control center, an asynchronous model predictive controller is proposed. Specifically, a dynamic controller, which can tune the performance online, is designed besides a traditional state feedback one. Even though such a combination may cause possible degradation of system performance, it can expand the initial feasible region and relieve the online computation burden efficiently. In addition, a decision variable is introduced to alleviate limitations on the feasible region generated by the constraints in the traditional MPC method. A series of solvable optimal problems are further constructed to achieve the desired performances. Finally, an application of the proposed method is given to demonstrate its effectiveness.
本文研究了基于模型预测控制(MPC)的异步攻击容忍控制方案,用于应对拒绝服务(DoS)攻击下的不确定马尔可夫跳跃网络物理系统(MJCPSs)。为解决控制中心可能无法观测到系统运行模式的问题,提出了一种异步模型预测控制器。具体而言,除了传统的状态反馈控制器外,还设计了一种能够在线调整性能的动态控制器。尽管这种组合可能会导致系统性能的潜在下降,但它可以扩大初始可行域并有效减轻在线计算负担。此外,引入了一个决策变量,以缓解传统MPC方法中约束条件对可行域产生的限制。进一步构建了一系列可解的最优问题,以实现期望的性能。最后,给出了所提方法的一个应用实例,以证明其有效性。