Adaptive wavelet neural network friction compensation of mechanical systems

Authors:
Shen-min Song;Zhuo-yi Song;Xing-lin Chen;Guangren Duan
Affiliations:
School of Astronautics, Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China;School of Astronautics, Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China;School of Astronautics, Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China;School of Astronautics, Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

Recently, based on multi-resolution analysis, wavelet neural networks (WNN) have been proposed as an alternative to NN for approximating arbitrary nonlinear functions in L2(R). Discontinuous friction function is an unavoidable nonlinear effect that can limit control performance in mechanical systems. In this paper, adaptive WNN is used to design a friction compensator for a single joint mechanical system. Then asymptotically stability of the system is assured by adding a PD controller and adaptive robust terms. The simulation results show the validity of the control scheme.