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Event-triggered adaptive prescribed-time control for nonlinear systems with uncertain time-varying parameters.

Authors :
Ning, Peng-Ju
Hua, Chang-Chun
Li, Kuo
Meng, Rui
Source :
Automatica. Nov2023, Vol. 157, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The problem of event-based adaptive prescribed-time control for a class of nonlinear systems with uncertain time-varying parameters is considered in this paper. The existence of uncertain time-varying parameters makes the system in question intrinsically different from that in prescribed-time stabilization or event-triggered control. Moreover, the existing prescribed-time control methods require the real-time continuous control input. For this reason, a novel event-based adaptive prescribed-time control strategy is presented by skillfully utilizing a key scaling technique and a new event-triggering mechanism. It is proved that the proposed event-triggering mechanism can enlarge the trigger time interval and effectively reduce the number of trigger moments compared with the existing event-triggered control methods. An important stability criterion is proposed based on the defined prescribed-time adjustment function. Furthermore, the proposed control algorithm can effectively reduce the computational burden and save the control effort. Finally, a numerical simulation verifies the effectiveness of the proposed prescribed-time control algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00051098
Volume :
157
Database :
Academic Search Index
Journal :
Automatica
Publication Type :
Academic Journal
Accession number :
171922085
Full Text :
https://doi.org/10.1016/j.automatica.2023.111229