Data‐Driven Hierarchical Performance Recovery Control for Cyber‐Physical Systems Against Sparse Actuator Attacks

This article proposes a data‐driven hierarchical performance recovery control method for cyber‐physical systems (CPSs) against sparse actuator attacks. First, two performance evaluators are constructed by selecting the tracking performance and stability of the system as key performance indicators. Then, the coprime factorization technique is utilized to construct the stable kernel representation (SKR) of the systems under nominal and attacked conditions in a data‐driven framework. In addition, according to different levels of the system performance degradation caused by the attacks, a performance‐based hierarchical resilient controller is designed to recover the system performance. Specifically, if the performance evaluator related to the tracking errors is violated, one controller parameter should be redesigned to recover the system performance. Otherwise, if the evaluator related to the stability is violated, it is necessary to redesign two control parameters to compensate for the negative effects of the attacks. Finally, the efficacy of the proposed method is demonstrated via a practical DC motor experiment.