Dynamic event-triggered control design for a class of p-normal nonlinear time-delay systems with actuator failures

Min Li, Jian Guo and Zhengrong Xiang

Applied Mathematics and Computation, 2022, vol. 421, issue C

Abstract: This paper investigates the adaptive tracking control problem for a class of p-normal nonlinear time-delay systems with actuator failures via a dynamic event-triggered strategy. To deal with the time-varying delay, a modified Lyapunov-Krasovskii functional (LKF) with the system powers is constructed. By using radial basis function neural networks and hyperbolic tangent function, the residual terms caused by the derivative of LKF can be handled. Then, to achieve better communication efficiency, a dynamic event-triggered strategy is proposed, in which the threshold parameter is dynamically adjusted with the change of the virtual control signal. With the help of the proposed adaptive controller, all states of the closed-loop system are bounded and a favorable tracking performance is ensured. Finally, two examples are given to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive neural networks; Actuator failures; Event-triggered; p-Normal nonlinear systems; Time-varying delays (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:421:y:2022:i:c:s0096300322000285

DOI: 10.1016/j.amc.2022.126942

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