Security Control for LPV System With Deception Attacks via Model Predictive Control: A Dynamic Output Feedback Approach
Security Control for LPV System With Deception Attacks via Model Predictive Control: A Dynamic Output Feedback Approach
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DOI：
10.1109/tac.2020.2984221
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发表时间：
2021-02
影响因子：
6.8
通讯作者：
Jun Wang;B. Ding;Jianchen Hu
中科院分区：
文献类型：
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作者：
Jun Wang;B. Ding;Jianchen Hu
研究了具有欺骗攻击、多面体不确定性和持续有界干扰的网络环境下系统的安全控制问题。由于状态不可测且考虑了物理约束，采用了输出反馈鲁棒模型预测控制。将之前关于输出反馈鲁棒MPC的研究结果扩展到欺骗攻击。为了描述闭环的稳定性，定义了均方二次有界性。提出了用线性矩阵不等式技术求解的优化问题。通过对状态估计误差集的简单更新，证明了优化问题是递归可行的，并且增广状态收敛到平衡点的邻域。通过数值仿真算例验证了所提理论方法的有效性。
This article considers security control under the network environment for a system with deception attacks, polytopic uncertainty, and persistent bounded disturbance. Since the state is immeasurable and the physical constraint is considered, the output feedback robust model predictive control (MPC) is utilized. The previous results on the output feedback robust MPC are extended to address the deception attacks. The mean-square quadratic boundedness is defined in order to characterize the closed-loop stability. An optimization problem is proposed, which can be solved by linear matrix inequality techniques. By a simple refreshment of the state estimation error set, the optimization problem is shown to be recursively feasible, and the augmented state converges to the neighborhood of equilibrium point. The effectiveness of the proposed theoretical approach is demonstrated by a numerical simulation example.