Abstract

Attainment of high-performance motion/velocity control objectives for the Direct-Drive Rotary (DDR) torque motor should fully consider practical nonlinearities in controller design, such as dynamic friction. The LuGre model has been widely utilized to describe nonlinear friction behavior; however, parameter identification for the LuGre model remains a challenge. A new dynamic friction parameter identification method for LuGre model is proposed in this study. Static parameters are identified through a series of constant velocity experiments, while dynamic parameters are obtained through a presliding process. Novel evolutionary algorithm (NEA) is utilized to increase identification accuracy. Experimental results gathered from the identification experiments conducted in the study for a practical DDR torque motor control system validate the effectiveness of the proposed method.

Highlights

  • The torque motor, especially Direct-Drive Rotary (DDR) torque motor, has been widely utilized in modern industry applications and features rotation blockage, soft mechanical properties, and a wide speed range [1, 2]

  • A new dynamic friction parameter identification method is proposed in this study for the LuGre model and an identification experiment is conducted for a practical DDR torque motor control system

  • The desired output angle for the DDR torque motor is given by a 1.0 Hz sinusoidal signal with 0.04 rad amplitude

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Summary

Introduction

The torque motor, especially Direct-Drive Rotary (DDR) torque motor, has been widely utilized in modern industry applications and features rotation blockage, soft mechanical properties, and a wide speed range [1, 2]. Designing a high-performance position/velocity tracking controller for the DDR torque motor [5] remains a challenge as multiple factors affecting control precision and dynamic nonlinear friction must be considered [6]. Dynamic friction nonlinearity may be addressed with a properly designed friction compensation controller. Effectiveness of the friction compensation controller is largely dependent on the friction model and accurate friction parameters [7]. The static model reflects the relationship between friction force and the relative movement speed consisting of several distinct parts including static friction, Coulomb friction, viscous friction, and the Stribeck curve effect. Effect of friction, when relative velocity between the two contact surfaces is zero, cannot be described by the static friction model

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