Predefined-Time Adaptive Neural Tracking Control for a Single Link Manipulator with an Event-Triggered Mechanism.
Sensors (Basel)
; 24(14)2024 Jul 15.
Article
in En
| MEDLINE
| ID: mdl-39065971
ABSTRACT
This paper introduces an adaptive trajectory-tracking control method for uncertain nonlinear systems, leveraging a time-varying threshold event-triggered mechanism to achieve predefined-time tracking. Compared to conventional time-triggering approaches, the employment of a time-varying threshold event-triggered mechanism significantly curtails communication resource wastage without compromising the system's performance. Furthermore, a novel adaptive control algorithm with predefined timing is introduced. This method guarantees that tracking errors converge to within a small vicinity of the origin within a predefined timeframe, ensuring all signals in the closed-loop system remain bounded. Moreover, by adjusting a controller-related parameter, we can predefine the upper bound of the convergence time. Finally, the efficacy of the control scheme is corroborated by simulation results obtained from a nonlinear manipulator system.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Sensors (Basel)
Year:
2024
Document type:
Article
Affiliation country:
China
Country of publication:
Switzerland