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Critic-only adaptive dynamic programming algorithms' applications to the secure control of cyber-physical systems

机译：仅限评估的自适应动态编程算法应用于网络物理系统的安全控制

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Industrial cyber-physical systems generally suffer from the malicious attacks and unmatched perturbation, and thus the security issue is always the core research topic in the related fields. This paper proposes a novel intelligent secure control scheme, which integrates optimal control theory, zero-sum game theory, reinforcement learning and neural networks. First, the secure control problem of the compromised system is converted into the zero-sum game issue of the nominal auxiliary system, and then both policy-iteration-based and value-iteration-based adaptive dynamic programming methods are introduced to solve the Hamilton-Jacobi-Isaacs equations. The proposed secure control scheme can mitigate the effects of actuator attacks and unmatched perturbation, and stabilize the compromised cyber-physical systems by tuning the system performance parameters, which is proved through the Lyapunov stability theory. Finally, the proposed approach is applied to the Quanser helicopter to verify the effectiveness. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.
机译：工业网络物理系统通常遭受恶意攻击和无与伦比的扰动，因此安全问题始终是相关领域的核心研究主题。本文提出了一种新颖的智能安全控制方案，其集成了最优控制理论，零和博弈理论，加固学习和神经网络。首先，受损系统的安全控制问题被转换为标称辅助系统的零和游戏问题，然后引入了基于策略的基于价值迭代的自适应动态编程方法来解决汉密尔顿 - Jacobi-Isaacs方程。所提出的安全控制方案可以减轻执行器攻击和无与伦比的扰动的影响，并通过调整系统性能参数来稳定受损的网络物理系统，这通过Lyapunov稳定性理论证明。最后，提出的方法应用于Quanser直升机以验证有效性。 （c）2019 ISA。 elsevier有限公司出版。保留所有权利。

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