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This paper investigates the secure control problem of networked control systems (NCSs) subject to partially unknown dynamics and network-injected attacks. To address these issues, a novel model-free online learning controller is proposed, which integrates adaptive dynamic programming (ADP) and sliding mode control (SMC) to eliminate reliance on accurate system models. The model-free SMC scheme is designed using only local state information and known bounds of disturbances/attacks, while ADP is employed to approximate optimal control policies. To further alleviate the communication burden of traditional SMC in networked environments, an event-triggered mechanism (ETM) is integrated into the control framework, yielding an ADP-based event-triggered sliding mode control (ETSMC) method, which combines ADP’s adaptive optimization and ETM’s communication efficiency. The proposed ADP-based ETSMC strategy guarantees the reachability of sliding surface and the asymptotic stability of sliding dynamics concurrently, avoiding the need for system identifiers or command generator models. Simulation results demonstrate that the proposed ETSMC ensures control performance and robustness while reducing communication burden, thereby verifying its feasibility and practicality.
Liu et al. (Wed,) studied this question.