JOURNAL ARTICLE

Adaptive Fault-Tolerant Formation Control of Heterogeneous Multi-Agent Systems under Directed Communication Topology

Shangkun LiuBin JiangZehui MaoYajie Ma

Year: 2022 Journal:   Sensors Vol: 22 (16)Pages: 6212-6212   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

This paper investigates the adaptive fault-tolerant formation control scheme for heterogeneous multi-agent systems consisting of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) with actuator faults, parameter uncertainties and external disturbances under directed communication topology. Firstly, the dynamic models of UAVs and USVs are introduced, and a unified heterogeneous multi-agent system model with actuator faults is established. Then, a distributed fault-tolerant formation controller is proposed for the unified model of UAVs and USVs in the XY plane by using adaptive updating laws and radial basis function neural network. After that, a decentralized formation-tracking controller is designed for the altitude control system of UAVs. Based on the Lyapunov stability theory, it can be proved that the formation errors and tracking errors are uniformly ultimately bounded which means that the expected time-varying formation is achieved. Finally, a simulation study is given to demonstrate the effectiveness of the proposed scheme.

Keywords:
Fault tolerance Control theory (sociology) Actuator Controller (irrigation) Multi-agent system Lyapunov function Control reconfiguration Bounded function Computer science Topology (electrical circuits) Lyapunov stability Fault detection and isolation Distributed computing Control engineering Engineering Control (management) Nonlinear system Artificial intelligence Mathematics

Metrics

13
Cited By
2.57
FWCI (Field Weighted Citation Impact)
47
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed Control Multi-Agent Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
UAV Applications and Optimization
Physical Sciences →  Engineering →  Aerospace Engineering
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering

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