Adaptive friction compensation with partially known dynamic friction model†

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Adaptive Control and Signal Processing Pub Date : 1998-12-04 DOI:10.1002/(SICI)1099-1115(199702)11:1<65::AID-ACS395>3.0.CO;2-3

C. Canudas de Wit, P. Lischinsky

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引用次数: 483

Abstract

This paper illustrates the application of a model-based adaptive friction compensation on a DC motor servomechanism. The dynamic friction model and the control structure studied previously by the authors were used as a basis for this study. The paper first proposes a two-step off-line method to estimate the nominal static and dynamic parameters associated with the model. Then two adaptive globally stable mechanisms are introduced to deal with structured normal forces and temperature variations. Assuming that a nominal friction model is known and that the friction variations can be suitably structured, adaptation is performed on the basis of only one parameter. The paper presents experimental results validating the identification of the dynamic friction model and the adaptive control scheme. These results show that the adaptive loop improves over a fixed compensation scheme and over a PID controller without friction compensation. © 1997 by John Wiley & Sons, Ltd.

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部分已知动态摩擦模型的自适应摩擦补偿

本文阐述了基于模型的自适应摩擦补偿在直流电机伺服机构中的应用。本文以作者之前研究的动态摩擦模型和控制结构为基础。本文首先提出了一种两步离线方法来估计与模型相关的标称静态和动态参数。然后引入了两种自适应全局稳定机制来处理结构法向力和温度变化。假设已知名义摩擦模型，并且可以适当地构造摩擦变化，则仅根据一个参数进行自适应。实验结果验证了动态摩擦模型的辨识和自适应控制方案。结果表明，该自适应回路比固定补偿方案和不加摩擦补偿的PID控制器的自适应回路性能更好。©1997 by John Wiley &儿子,有限公司

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.