Modeling of Electro-hydraulic Position Servo System of Pump-Controlled Cylinder Based on HHGA-RBFNN

被引:0
|
作者
Gao Qiang [1 ]
Ji Li-jun [1 ]
Hou Yuan-long [1 ]
Tong Zhong-zhi [1 ]
Jin Yong [2 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing, Peoples R China
[2] Mil Representat Off Gen Armaments, Dept Wuhan Area, Wuhan, Peoples R China
来源
2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC) | 2011年
关键词
Pump-controlled cylinder; HHGA (Hybrid Hierarchy Genetic Algorithm); RBFNN (Radial Basis Function Neural Network); NEURAL-NETWORK;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:335 / 339
页数:5
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