Partition Compensation Algorithm for Friction Based on Adaptive Fuzzy Neural Network

Author

Jiang, Yu ; Cao, Jun ; Yang, Guo-hui

Author_Institution

Inf. & Commun. Eng. Coll., Harbin Eng. Univ.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

1930

Lastpage

1935

Abstract

For nonlinear friction force in hydraulic position tracking system, partition compensation is employed to solve the problem of large approximation error caused by non-smooth characteristic of friction when the friction is compensated globally by fuzzy neural network (FNN). The experimental results show that the partition compensation algorithm is effective in compensating the nonlinearity, and the system has good steady-state tracking performance

Keywords

friction; fuzzy neural nets; hydraulic systems; neurocontrollers; position control; tracking; adaptive fuzzy neural network; approximation error; hydraulic position tracking system; nonlinear friction force; partition compensation algorithm; Adaptive systems; Cybernetics; Educational institutions; Forestry; Friction; Fuzzy neural networks; Machine learning; Microwave communication; Microwave technology; Microwave theory and techniques; Neural networks; Nonlinear dynamical systems; Partitioning algorithms; Servomechanisms; Hydraulic position tracking system; adaptive fuzzy neural network; partition compensation;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259120

Filename

4028381