Multi-Joint Servo Systems with Backlash Compensation and Input Constraints

DOI

10.2991/emcs-17.2017.217How to use a DOI?

Keywords

Backlash nonlinearity; Convergence; Iterative learning control; input constraints; Backstepping control;

Abstract

Abstract. To improve the robustness and accuracy of the traditional backstepping control, a iterative learning control is proposed and the PMSM servo actuator system is modeled. The dead-zone model is approximated by a continuously differentiable functions,in which the fitting errors and model uncertainties are regarded as disturbance-like terms. Therefore,the continuous nonlinear model with uncertain perturbation can achieve accurate compensation of backlash nonlinearity. The finite-time convergence condition of the closed-loop system has been proved by the Lapunov theory. The result shows that the tracking error converge to an arbitrarily small residual within finite time and achieve the precise compensation of the backlash.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fei Xu
AU  - Liping Wang
PY  - 2017/03
DA  - 2017/03
TI  - Multi-Joint Servo Systems with Backlash Compensation and Input Constraints
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 1130
EP  - 1134
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.217
DO  - 10.2991/emcs-17.2017.217
ID  - Xu2017/03
ER  -