DocumentCode
2196643
Title
Modeling of electro-hydraulic position servo system of pump-controlled cylinder based on HHGA-RBFNN
Author
Qiang, Gao ; Li-jun, Ji ; Yuan-long, Hou ; Zhong-zhi, Tong ; Yong, Jin
Author_Institution
Sch. of Mech. Eng. Nanjing, Univ. of Sci. & Technol., Nanjing, China
fYear
2011
fDate
9-11 Sept. 2011
Firstpage
335
Lastpage
339
Abstract
To solve the problem that it is difficult to construct an exact mathematic model for the electro-hydraulic position servo system of a pump-controlled cylinder with nonlinearity and time- varying property, HHGA-RBFNN is proposed. Each chromosome only contains three parameters including the number of hidden nodes, center and width of radial basis function; so that the complexity of proposed algorithm could be decreased with the optimal solution converged. By coding the center and width of the radial basis function respectively, the convergence rate of the algorithm could be improved; by considering both the number of hidden nodes and root-mean-square error for the selection of fitness function, the structure and parameters of network are optimized simultaneously. The simulation and experimental results show that the proposed algorithm has high modeling accuracy, excellent generalization and fast convergence rate. The simulation and experimental results show that the proposed algorithm is valid and accurate.
Keywords
control engineering computing; electrohydraulic control equipment; genetic algorithms; mean square error methods; position control; pumps; radial basis function networks; servomechanisms; HHGA- RBFNN; electro-hydraulic position servo system modelling; fitness function; hybrid hierarchy genetic algorithm; nonlinearity property; pump-controlled cylinder; radial basis function center; radial basis function hidden node; radial basis function neural network; radial basis function width; root-mean-square error; time-varying property; Biological cells; Convergence; Encoding; Genetic algorithms; Servomotors; Testing; Training; HHGA (Hybrid Hierarchy Genetic Algorithm); Pump-controlled cylinder; RBFNN (Radial Basis Function Neural Network);
fLanguage
English
Publisher
ieee
Conference_Titel
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location
Ningbo
Print_ISBN
978-1-4577-0320-1
Type
conf
DOI
10.1109/ICECC.2011.6067769
Filename
6067769
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