Robust boundary control approaches to the stabilization of the Euler–Bernoulli beam under external disturbances

Author:

Wang Yingying12ORCID,Wu Wei12ORCID,Wang Zhan12,Lou Xuyang12,Görges Daniel3ORCID

Affiliation:

1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, China

2. School of IoT Engineering, Jiangnan University, Wuxi, China

3. Department of Electrical and Computer Engineering, University of Kaiserslautern, Kaiserslautern, Germany

Abstract

In this paper, the boundary feedback control problem for the Euler–Bernoulli beam with unknown time-varying distributed load and boundary disturbance is investigated. Based on the Lagrangian–Hamiltonian mechanics, the model of the beam is derived as a partial differential equation. To suppress the external disturbance, two disturbance rejection control approaches are adopted in the control design. Firstly, a disturbance observer is designed to estimate the boundary disturbance online. Thus, the effect of the boundary disturbance can be canceled directly in the feedback loop. A time-varying function is applied in the disturbance observer to prevent an excessively large control input. Secondly, a new observer is developed to estimate the upper bound of the disturbance and a sign function is introduced to suppress the influence of the disturbance without demanding the boundedness of the derivative of the boundary disturbance. The well-posedness and the uniform boundedness of the closed-loop system are proved using the operator semigroup theory and the Lyapunov method. Numerical comparisons with existing results are made for demonstrating the advantages of the proposed approaches.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Robust adaptive vibration control of a gantry crane system with flexible cable;International Journal of Adaptive Control and Signal Processing;2023-12-12

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