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Adaptive Sliding Mode Control for Optimal ℒ2-gain Performance of Interconnected Large-scale Cyber Physical Systems Under FDIAs Environments

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  • Control Theory and Applications
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Abstract

Aiming at a class of large-scale cyber physical systems (LSCPSs) with multiple subsystems nonlinearly interconnected under false data injection attacks (FDIAs), the problems of ℒ2-gain performance analysis and sliding mode control are studied. First, the quadratical stability criteria with ℒ2-gain performance of the sliding dynamics of LSCPSs are derived by linear matrix inequalities (LMIs) technology. Then adaptive integral sliding mode controllers are designed, which include two parts: one part is designed for suppressing the influences of FDIAs on the systems, and the other part is used to deal with factors such as quantization errors, external interferences, nonlinear interconnections, and model uncertainties. Finally, the comparison results of simulation examples show the effectiveness and superiority of the established methods.

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Data Availability Statement

All data generated or analysed during this study are included in this published article.

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Authors and Affiliations

  1. CICAEET, the School of Automation, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, 210044, China

    Bo-Chao Zheng, Chen Lai & Tao Li

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  1. Bo-Chao Zheng
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  2. Chen Lai
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Correspondence to Bo-Chao Zheng.

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This work was supported in part by National Natural Science Foundation of China (No. 61973169,61973168), the Natural Science foundation of Jiangsu Province (No. BK20201392), The 333 Project of Jiangsu Province (No. 2020067) and Qing Lan Project of Jiangsu Province (No. R2021Q04). We especially thank Dr. Guoying Miao for her knowledge and help in revising several questions of this paper.

Bo-Chao Zheng received his Ph.D. degree in control theory and control engineering from Northeastern University, Shenyang, China, in 2012. In 2014, he was a Visiting Research Fellow with Department of Electrical Engineering, Yeungnam University, Kyongsan, Korea, for two months. From 2016 to 2017, he was a Visiting Academic with the School of Engineering, RMIT University, Melbourne, VIC, Australia, for one year. He is currently a Professor with the School of Automation, Nanjing University of Information Science and Technology, Nanjing, China. His current research interests include sliding mode control, quantized control, Markov jump systems, and fuzzy control systems.

Chen Lai received her bachelor’s degree in electronic information and engineering from Jiangxi Agricultural University, China, in 2020. Now, she is studying for a master’s degree in the School of Automation, Nanjing University of Information Science and Technology, Nanjing, China. Her research interests include sliding mode control, cyber physical system, and securing control.

Tao Li received his Ph.D. degree from Southeast University, Nanjing, China. He is currently a Professor with the Nanjing University of Information Science and Technology, Nanjing. He completed the Visiting Scholar fellowships with the University of Alberta, Canada, the University of Western Sydney, Australia, the University of Hong Kong and the City University of Hong Kong. He has authored or coauthored more than 70 papers in journals including Automatica, IEEE Transactions on Neural Networks, and IEEE Transactions on Systems, Man, and Cybernetics: Systems. His current research interests include fault detection and fault-tolerant control for time-delay systems.

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Zheng, BC., Lai, C. & Li, T. Adaptive Sliding Mode Control for Optimal ℒ2-gain Performance of Interconnected Large-scale Cyber Physical Systems Under FDIAs Environments. Int. J. Control Autom. Syst. 21, 2566–2576 (2023). https://doi.org/10.1007/s12555-022-0242-1

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