Input delay compensation of nonlinear systems with uncertain time-varying parameters

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

European Journal of Control Pub Date : 2024-08-31 DOI:10.1016/j.ejcon.2024.101100

Ashish Kumar Jain

引用次数: 0

Abstract

A robust adaptive control law is designed for the class of nonlinear systems with uncertain time-varying parametric dynamics and input delays. The Constitution of control law design is based on filtered tracking errors, previous values of control input and estimate of uncertain parameters which is updated by the update law. An arbitrary large input delay compensation is guaranteed by deriving sufficient control gain conditions using Lyapunov–Krasovskii based stability analysis. The efficacy of the design is verified by Simulation results of two-link robot manipulator dynamical system.

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具有不确定时变参数的非线性系统的输入延迟补偿

为一类具有不确定时变参数动态和输入延迟的非线性系统设计了鲁棒自适应控制法则。控制律设计的基础是滤波跟踪误差、控制输入的先前值以及由更新律更新的不确定参数的估计值。通过使用基于 Lyapunov-Krasovskii 稳定性分析法推导出充分的控制增益条件，保证了对任意大输入延迟的补偿。双链机器人机械手动力系统的仿真结果验证了设计的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.