Title :
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.
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.259120
