LMI-based robust adaptive neural network control for Euler–Bernoulli beam with uncertain parameters and disturbances. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Xing, Xueyan; Yang, Hongjun; Liu, Jinkun; Wang, Shuquan
• Is Part Of: International journal of control. Volume 95:Issue 1(2022)
• Page Start: 1
• Page End: 10
• Publication Date: 2022-01-02
• Subjects: Distributed parameter systems -- boundary control -- LMIs -- robust adaptive neural network control; Automatic control -- Periodicals; Electronic journals; 629.8
• DOI: 10.1080/00207179.2020.1775306
• Languages: English
• ISSNs: 0020-7179

Abstract

Abstract : This paper is concerned with the stabilisation problem of an Euler–Bernoulli beam with uncertain parameters and disturbances. To correctly represent the beam's behaviour, the partial differential equations model is utilised for the control design of the beam without missing any high-order mode information. Then the linear matrix inequalities (LMIs) method is applied to the robust adaptive neural network control design to cope with systematic uncertainties and stabilise the beam system with disturbance compensation. Through resolving LMIs, feasible sets of designed control parameters can be effectively obtained without model linearisation. Finally, numerical simulations are done to validate the effectiveness of the proposed control.