Abstract
In this paper, an adaptive practical prescribed-time consensus (PPTC) for multiple mechanical systems with full-state constraints is discussed. We first propose a new nonlinear mapping (NM). By transforming the full state–constrained system with the NM, we can obtain an unconstrained system. Then combined with neural networks, graph theory, and practical prescribed-time control theory, a distributed adaptive PPTC protocol is proposed for the unconstrained system, which can ensure that position errors and speed errors reach a certain region within a prescribed-time and full-state constraints are satisfied. Finally, an example is given to demonstrate that this method can be implemented.
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 callMore From: Transactions of the Institute of Measurement and Control
Disclaimer: 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.
