Distributed Adaptive Consensus Tracking Control for Multi-Agent System With Communication Constraints

Aiming at a class of high-order strict feedback nonlinear multi-agent systems with communication constraints, a novel distributed adaptive back-stepping control method is proposed to cooperatively track the moving targets. First, five agents are used as controlled objects, and all five agents form a...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2021-06, Vol.32 (6), p.1293-1306
Main Authors: Zhang, Pu, Xue, Huifeng, Gao, Shan, Zhang, Jialong
Format: Article
Language:English
Subjects:
Adaptive control
back-stepping technology
Communications systems
Control methods
Control systems design
Convergence
Moving targets
multi-agent system
Multi-agent systems
Multiagent systems
Nonlinear systems
Process control
rapid convergence
Target tracking
Time-varying systems
Topology
Tracking
Tracking control
Tracking errors
Trajectory
Trajectory optimization
Weak communication
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Summary:Aiming at a class of high-order strict feedback nonlinear multi-agent systems with communication constraints, a novel distributed adaptive back-stepping control method is proposed to cooperatively track the moving targets. First, five agents are used as controlled objects, and all five agents form a "leader-follower" mode with a distributed control structure. Meanwhile, the leader's moving velocity is considered the forward velocity of the whole formation system, and remaining agents follow the leader's movement. Then, each agent tracks the desired formation with a time-varying reference trajectory, thereby achieving the consensus tracking purpose of multi-agent system. Moreover, the multi-agent formation system avoids obstacles with the optimal trajectory and maintains the desired formation movement. Finally, the simulation results show that the designed controller can achieve the lateral and horizontal tracking errors of the multi-agent system to converge quickly, and then keep the system asymptotically stable during tracking process.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2020.3048383