A Robust Nonlinear Model Reference Adaptive Control for Disturbed Linear Systems: An LMI Approach

• 成果类型: Article
• 署名作者: Franco, Roberto; Rios, Hector; de Loza, Alejandra Ferreira; Efimov, Denis
• 署名单位: Consejo Nacional de Ciencia y Tecnologia (CONACyT); Universite de Lille; Centrale Lille; Inria; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Information Sciences & Technologies (INS2I)
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3069719
• 发表日期: 2022
• 页码: 1937-1943
• 关键词: Perturbation methods; CONVERGENCE; Adaptation models; Linear systems; Adaptive control; uncertain systems; simulation; model reference adaptive control (MRAC); nonlinear control; Robust control; uncertain linear systems

摘要

In this article, a robust nonlinear model reference adaptive control (MRAC) is proposed for disturbed linear systems, i.e., linear systems with parameter uncertainties, and external time-dependent perturbations or nonlinear unmodeled dynamics matched with the control input. The proposed nonlinear control law is composed of two nonlinear adaptive gains. Such adaptive gains allow the control to counteract the effects of some perturbations and nonlinear unmodeled dynamics ensuring asymptotic convergence of the tracking error to zero, and the boundedness of the adaptive gains. The nonlinear controller synthesis is given by a constructive method based on the solution of linear matrix inequalities. Besides, the simulation results show that, due to the nonlinearities, the rate of convergence of the proposed algorithm is faster than that provided by a classic MRAC.