Abstract
The dynamic event-triggered (DET) formation control problem of a class of stochastic nonlinear multi-agent systems (MASs) with full state constraints is investigated in this article. Supposing that the human operator sends commands to the leader as control input signals, all followers keep formation through network topology communication. Under the command-filter-based backstepping technique, the radial basis function neural networks (RBF NNs) and the barrier Lyapunov function (BLF) are utilized to resolve the problems of unknown nonlinear terms and full state constraints, respectively. Furthermore, a DET control mechanism is proposed to reduce the occupation of communication bandwidth. The presented distributed formation control strategy guarantees that all signals of the MASs are semi-globally uniformly ultimately bounded (SGUUB) in probability. Finally, the feasibility of the theoretical research result is demonstrated by a simulation example.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
