Security Control for LPV System With Deception Attacks via Model Predictive Control: A Dynamic Output Feedback Approach

• 成果类型: Article
• 署名作者: Wang, Jun; Ding, Baocang; Hu, Jianchen
• 署名单位: Xi'an Jiaotong University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.2984221
• 发表日期: 2021
• 页码: 760-767
• 关键词: Deception attacks; Output feedback; recursive feasibility; robust model predictive control (MPC); security control

摘要

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.