Analysis of Position Servo System of Pneumatic Manipulator Based on RBF Neural Network PID Control

This paper analyzes the characteristics of pneumatic position servo system of a mechanical hand in particularly respect to the nonlinearity of the position servo system of a pneumatic manipulator with 3 degrees of freedom. A pneumatic position servo model was developed in AMESim and imported into Si...

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Bibliographic Details
Published in2010 International Conference on Web Information Systems and Mining Vol. 2; pp. 221 - 226
Main Authors Ruibo Yuan, Chungeng Sun, Shaonan Ba, Zongcheng Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2010
Subjects
Artificial neural networks
co-simulation
Computational modeling
Manipulators
Mathematical model
PID control
Pneumatic position servo systems
Pneumatic systems
RBF neural network control
Servomotors
Valves
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Summary:This paper analyzes the characteristics of pneumatic position servo system of a mechanical hand in particularly respect to the nonlinearity of the position servo system of a pneumatic manipulator with 3 degrees of freedom. A pneumatic position servo model was developed in AMESim and imported into Simulink in the form of a S-function, resulting in a RBF neural network PID control system model in Simulink. Co-simulations were performed with both AMESim and Matlab/Simulink. As compared to the simulation results of the same system with AMESim model without correction, RBF neural network PID controller significantly improves the dynamic performance of the pneumatic servo system.
ISBN:1424484383
9781424484386
DOI:10.1109/WISM.2010.171