Regular Papers

International Journal of Control, Automation and Systems 2023; 21(1): 84-93

Published online January 6, 2023

https://doi.org/10.1007/s12555-021-0921-3

© The International Journal of Control, Automation, and Systems

Dynamic Event-triggered Adaptive Control for Uncertain Nonlinear Switched Systems Based on MDADT Method

Xueliang Wang, Jianwei Xia*, Na Zhang, Miao Yu, and Xiaoxiao Guo

Liaocheng University

Abstract

This article deals with the dynamic event-triggered tracking control problem for nonlinear switched systems with uncertain nonlinearities. By combining neural network control technology, mode-dependent average dwell time (MDADT) switching rule and dynamic event-triggered strategy, a valid adaptive control scheme is established, which guarantees the boundedness of all signals in the resulting closed-loop system and the tracking error eventually converges to a small neighborhood of the origin under a class of switching signals with MDADT property. Unlike the existing tracking control schemes, the proposed dynamic event-triggered strategy reduce some unnecessary transmissions from controller to actuator and thus saving network resources better. Finally, the effectiveness of the proposed control design is verified by a numerical simulation.

Keywords Dynamic event-triggered mechanism, mode-dependent average dwell time, neural network, switched nonlinear systems.

Article

Regular Papers

International Journal of Control, Automation and Systems 2023; 21(1): 84-93

Published online January 1, 2023 https://doi.org/10.1007/s12555-021-0921-3

Copyright © The International Journal of Control, Automation, and Systems.

Dynamic Event-triggered Adaptive Control for Uncertain Nonlinear Switched Systems Based on MDADT Method

Xueliang Wang, Jianwei Xia*, Na Zhang, Miao Yu, and Xiaoxiao Guo

Liaocheng University

Abstract

This article deals with the dynamic event-triggered tracking control problem for nonlinear switched systems with uncertain nonlinearities. By combining neural network control technology, mode-dependent average dwell time (MDADT) switching rule and dynamic event-triggered strategy, a valid adaptive control scheme is established, which guarantees the boundedness of all signals in the resulting closed-loop system and the tracking error eventually converges to a small neighborhood of the origin under a class of switching signals with MDADT property. Unlike the existing tracking control schemes, the proposed dynamic event-triggered strategy reduce some unnecessary transmissions from controller to actuator and thus saving network resources better. Finally, the effectiveness of the proposed control design is verified by a numerical simulation.

Keywords: Dynamic event-triggered mechanism, mode-dependent average dwell time, neural network, switched nonlinear systems.

IJCAS
September 2024

Vol. 22, No. 9, pp. 2673~2953

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