期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 32, 期 2, 页码 639-652出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2020.2978854
关键词
Directed communication networks; fixed-time consensus tracking; neural networks (NNs); nonlinear multiagent systems
类别
资金
- National Natural Science Foundation of China [61621004, 61420106016]
- Research Fund of State Key Laboratory of Synthetical Automation for Process Industries [2018ZCX03]
This article proposes a distributed control strategy based on fixed-time observer for solving the problem of consensus tracking in nonlinear multiagent systems. In this strategy, follower systems have unknown nonlinear functions and time-varying disturbances, and the tracking errors converge into a small set near zero within a fixed time.
This article investigates the problem of fixed-time consensus tracking for nonlinear multiagent systems. Different from the existing studies where the follower systems are linear or pure integrator-type systems, in this article, the follower systems have completely unknown nonlinear functions and time-varying disturbances. Within this framework, a fixed-time observer-based distributed control strategy is proposed to realize the consensus tracking. First, a distributed fixed-time observer is designed for each follower to estimate the leader's state under directed networks. Then, based on the estimate, a fixed-time tracking control protocol is developed where novel approximation and estimation schemes are designed to tackle the nonlinear functions and disturbances. Furthermore, under the proposed control strategy, it is proved that the tracking errors converge into a small set near zero with a fixed-time convergence rate. Finally, the validity of the proposed method is verified by the simulation results.
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