RISE-based asymptotic adaptive prescribed performance control of uncertain nonlinear systems and application to DC motor

IF 2.5 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control Pub Date : 2025-01-01 DOI:10.1016/j.ejcon.2024.101168

Zhangbao Xu , Maokun Zhang , Jialin Ren , Zhenle Dong , Jianyong Yao

引用次数: 0

Abstract

In this study, the asymptotic control of a class of uncertain nonlinear systems is investigated and a robust integral of the sign of the error (RISE)-based asymptotic adaptive prescribed performance controller is developed, where adaptive control for unknown parameters and RISE for disturbances are combined via backstepping design, ensuring the asymptotic stability of the closed-loop system. While, a simple error transformation function is constructed with the prescribed performance function, and improved tracking precision with prescribed control performance is guaranteed. Finally, the proposed method is applied to the DC motor system and comparative experimental results are obtained to verify its effectiveness.

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来源期刊

European Journal of Control 工程技术-自动化与控制系统

CiteScore

5.80

自引率

5.90%

发文量

131

审稿时长

1 months

期刊介绍： The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field. The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering. The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications. Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results. The design and implementation of a successful control system requires the use of a range of techniques: Modelling Robustness Analysis Identification Optimization Control Law Design Numerical analysis Fault Detection, and so on.