| 摘要: |
| In this paper, we present an output regulation method for unknown cyber-physical systems (CPSs) under time-delay attacks in both the sensor-to-controller (S-C) channel and the controller-to-actuator (C-A) channel. The proposed approach is designed using control inputs and tracking errors which are accessible data. Reinforcement learning is leveraged to update the control gains in real time using policy or value iterations. A thorough stability analysis is conducted and it is found that the proposed controller can sustain the convergence and asymptotic stability even when two channels are attacked. Finally, comparison results with a simulated CPS verify the effectiveness of the proposed output regulation method. |
| 关键词: Adaptive output regulation · Cyber-physical systems · Time-delay attacks · Reinforcement learning |
| DOI：https://doi.org/10.1007/s11768-021-00072-w |
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| 基金项目:This work was supported by the National Natural Science Foundation of China (Nos. 61973277, 62073292) and in part by the Zhejiang Provincial Natural Science Foundation of China (No. LR20F030004). |
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| Adaptive output regulation for cyber-physical systems under time-delay attacks |
| Dan Jin1,Bo Chen1,Li Yu1,Shichao Liu2 |
| (1 Zhejiang University of Technology;2 Carleton University) |
| Abstract: |
| In this paper, we present an output regulation method for unknown cyber-physical systems (CPSs) under time-delay attacks in both the sensor-to-controller (S-C) channel and the controller-to-actuator (C-A) channel. The proposed approach is designed using control inputs and tracking errors which are accessible data. Reinforcement learning is leveraged to update the control gains in real time using policy or value iterations. A thorough stability analysis is conducted and it is found that the proposed controller can sustain the convergence and asymptotic stability even when two channels are attacked. Finally, comparison results with a simulated CPS verify the effectiveness of the proposed output regulation method. |
| Key words: Adaptive output regulation · Cyber-physical systems · Time-delay attacks · Reinforcement learning |
