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Resilient iterative learning control for a class of discrete-time nonlinear systems under hybrid attacks |
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| Authors: | Xuyang Zhao Yanling Yin Xuhui Bu |
| Affiliation: | 1. Research Center for Energy Economics, School of Business Administration, Henan Polytechnic University, Jiaozuo, China School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China Contribution: Formal analysis, Investigation, Methodology, Validation;2. Research Center for Energy Economics, School of Business Administration, Henan Polytechnic University, Jiaozuo, China;3. School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Henan Polytechnic University, Jiaozuo, China |
| Abstract: | The security control problem for a class of unknown nonlinear systems is considered in this paper. For the nonlinear system running in the network environment, the measurement channel is subjected to hybrid attacks. Intermittent denial of service attacks and false data injection attacks are modeled as the hybrid attacks. According to the characteristics of the repetitive system, a resilient iterative learning control (ILC) algorithm under hybrid attacks is devised. Subsequently, the stability of the system is proved by mathematical derivation and theoretical analysis in the sense of mathematical expectation. The theoretical analysis results indicate that the resilient ILC algorithm can ensure the stability of the system, and the tracking error converges with the increased number of iterations. Finally, the validity of the algorithm is illustrated by numerical simulation and mobile robot simulation. |
| Keywords: | iterative learning control networked control systems hybrid attacks nonlinear systems resilient design |