Abstract

The fast finite-time event-triggered consensus control is investigated for a category of uncertain nonlinear multiagent systems (MASs) with full-state constraints. The uncertainty of the system is estimated by the radial basis function neural networks (RBFNNs). Furthermore, to achieve the fast finite-time stability and not violate the full-state constraints, a fast finite-time event-triggered consensus control method is proposed. The proposed control method can achieve the fast finite-time stability of the system, and all the followers can track the output signal of the leader. Meanwhile, the system states do not exceed the boundaries of the full-state constraints, and the communication resources of the system can be saved. Finally, some simulation examples are provided to verify the feasibility of the proposed approach.

Full Text
Published version (Free)

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 call