Year: 2025
Type: article
Abstract: This article deals with the distributed event-triggered feedback stabilization for an Euler–Bernoulli beam equation. Novel event-triggered rules with distributed damping control laws are proposed to stabilize the beam system: one rule is built based on the beam energy and the other on the beam state information plus an exponentially time-decreasing term to reduce the switching frequency of actuators. Well-posedness and no Zeno behaviour are completely proven for our event-triggered sampled feedback control systems. Moreover, by developing Lyapunov functionals, sufficient LMI-type conditions on the system parameters are proposed to ensure exponential stabilization of the event-triggered feedback beam system. On the other hand, we show that the exponential stabilization is not achievable by using the periodic sampled feedback control laws (i.e., constant sample and hold) no matter what the sampling period is. Numerical simulations are presented to validate the stabilization performance of our proposed event-triggered control strategy.
DOI: 10.1051/cocv/2025065
Authors: Xueru Fan, Cheng-Zhong Xu, Hua-Cheng Zhou, Weiwei Hu, Chunhai Kou
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid:
Awards: G2496939947, G3010527862, G3100320077, G3962853814, Nonlinear Control and Observer Designs for Flow-Transport Systems, Observer Design for Infinite dimensional SyStEm, Collaborative Research: AMPS: Deep-Learning-Enabled Distributed Optimization Algorithms for Stochastic Security Constrained Unit Commitment
OpenAlex ID: W4412899725