Adaptive friction compensation with partially known dynamic friction model

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.

Design and structural performance measurements of a novel multi-cantilever foil bearing

“…The results can be explained by regarding the underlying foil structure as a dry-friction system in the identification procedure. As reported in De Wit and Lischinsky 28 for a Coulomb friction system, the equivalent viscous damping can be obtained from 4μFn/πω0X , indicating that the damping coefficient is inversely proportional to the excitation frequency and motion amplitude.…”

Identification of multiple mode models via Distributed Particle Swarm Optimization

“…Then, an experimental validation using a DC motor system is presented to confirm the effectiveness of the proposed identification method. Note that DC motor systems that are common components in many practical control systems usually have non-linear friction whose modeling has always been a difficult and challenging problem (see Armstrong-Héouvry et al, 1994;Taghirad and Bélanger, 1998;Bai, 1997;de Wit and Lischinsky, 1997). In this experiment, a set of subsystems of PWA models is identified via the proposed distributed PSO method, which verifies its powerful and practical applicability.…”

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