Dynamic event‐triggered dissipative control of nonlinear networked control systems with deception attacks

In this article, the hybrid‐triggered predictive control of cyber‐physical systems (CPSs) under cyber‐attacks is researched. Firstly, considering the unpredictable state of the CPSs, an observer‐based model is constructed, and the predictor is put forward to predict state. Secondly, a hybrid‐triggered scheme is adopted to avoid unnecessary‐data transmission by introducing a hybrid switch mode. Thirdly, the deception attacks and DoS attacks are existed in sensor‐to‐observer (S‐O) and observer‐to‐controller (O‐C), separately. Two types of attack modeling are established based on their characteristics. With the proposed control method, some sufficient conditions are obtained to ensure the input‐to‐state stability (ISS) of CPSs. Finally, the results of simulation examples are received to testify the advantage of developed control strategy.

Hybrid‐triggered predictive control of cyber‐physical‐systems under cyber‐attacks

Li,

Zhan,

et al. 2024

Cooperative output regulation of heterogeneous multi‐agent systems under false data injection attacks

Geng,

Zhao

2024

This paper studies the cooperative output regulation problem for heterogeneous multi‐agent systems (MASs) subject to false data injection (FDI) attacks, which means the malicious cyber‐attackers may inject false data into the communication topology randomly. To ensure that each follower agent can track the leader agent accurately, we construct both an observer and a control law for each follower agent. Since the FDI attacks may exist in the communication network, a filter with an adaptive compensator, which can estimate attack signals dynamically, is equipped for each observer, such that the filter can neutralize attacks when malicious attackers launch attacks. Therefore, the cooperative output regulation can be achieved under the control law based on the observer no matter whether there exist attacks or not. Finally, a numerical example is provided for validating the theoretical results.

Linear convergence of event‐triggered distributed optimization with metric subregularity condition

Yu,

Cheng,

Qiu

et al. 2024

This paper designs a continuous‐time algorithm with event‐triggered communication (ETC) for solving a class of distributed convex optimization problems with a metric subregularity condition. First, we develop an event‐triggered continuous‐time optimization algorithm to overcome the bandwidth limitation of multi‐agent systems. Besides, with the aid of Lyapunov theory, we prove that the distributed event‐triggered algorithm converges to the optimum set with an exact linear convergence rate, without the strongly convex condition. Moreover, we provide the discrete version of the continuous‐time algorithm and show its exact linear convergence rate. Finally, we give a comparison example to validate the effectiveness of the designed algorithm in communication resource saving.