Funnel-based optimized formation control for MIMO multi-agent systems under DoS attacks: A DETM quantized method

• Published in: IEEE internet of things journal p. 1
• Main Authors: Xu, Ning, Gao, Zhen, Zhao, Ning, Zhang, Liang
• Format: Journal Article
• Language: English
• Published: IEEE 09.10.2025
• Subjects: Artificial neural networks; Denial-of-service attack; denial-of-service attacks; Event detection; event-triggered control; Formation control; Multi-agent systems; Nonlinear dynamical systems; Optimal control; Quantization (signal); Reinforcement learning; Security; Vectors
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2025.3617923

Combining reinforcement learning (RL) and quantization methods, this article addresses the formation control problem for a class of multi-input multi-output (MIMO) nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks. Since the information exchange between agents is destroyed by DoS attacks, the leader's information becomes unavailable. Thus, a distributed formation estimator is designed to obtain the leader's state. Next, by constructing an logarithmic quantizer, a new dynamic event-triggered quantized control strategy is studied to save communication resources. In order to satisfy both transient and steady-state performances, an improved funnel function is embedded in controller design. In addition, based on optimized backstepping technique, an actor-critic architecture is established to achieve optimized secure formation control by RL method. Finally, the simulation results verify the effectiveness of proposed control scheme.