Work

Neuroadaptive fault-tolerant bipartite output formation control for stochastic nonlinear heterogeneous multi-agent systems with multiple leaders and Markovian switching topologies

Year: 2026

Type: article

Abstract: This paper studies fault-tolerant bipartite time-varying output formation (BTVOF) control for stochastic nonlinear heterogeneous multi-agent systems (SNHMASs) with multiple leaders. The interaction topology is signed and switches according to a Markov process, and followers may suffer actuator loss-of-effectiveness faults. We design a distributed leader-state compensator and, for each follower, an output-based observer. Unknown nonlinearities are approximated by adaptive neural networks (NNs) using only local output measurements. Building on these components, we develop a distributed fault-tolerant controller that achieves the desired BTVOF pattern despite stochastic disturbances, nonlinear dynamics, and actuator faults. Rigorous Lyapunov analysis demonstrates that all tracking errors are uniformly ultimately bounded (UUB) in the mean square sense. Simulation results are provided to validate the effectiveness of the proposed control strategy.

Source: Transactions of the Institute of Measurement and Control

DOI: 10.1177/01423312261422655

Authors: Xin Li, Jie Wu, Xisheng Zhan, Lingli Cheng, Qingsheng Yang

Institution: Hubei Normal University

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: National Natural Science Foundation of China, Natural Science Foundation of Hubei Province

Awards: G2281153890, G5661206772, G5729443646