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

2010 ◽  
Author(s):  
Ruibo Yuan ◽  
Chungeng Sun ◽  
Shaonan Ba ◽  
Zongcheng Zhang
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Rbf Neural Network ◽  
Servo System ◽  
Position Servo ◽  
Neural Network Pid

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

2010 ◽  
Vol 40-41 ◽  
pp. 65-70 ◽  
Author(s):  
Jing Luo ◽  
Rui Bo Yuan ◽  
Yu Bi Yuan ◽  
Shao Nan Ba ◽  
Zong Cheng Zhang
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Hybrid Control ◽  
Rbf Neural Network ◽  
Servo System ◽  
Fast Response ◽  
Quick Response ◽  
Pneumatic Servo System ◽  
The Stability ◽  
Neural Network Pid

Through analysis and comparison of simple PID control and RBF neural network-PID hybrid control of the pneumatic servo system, then compared the stability and quick response under the two control system. Concluded that RBF neural network-PID hybrid control has better stability and fast response than the simple PID control.

Neural Network PID Control Application of Hydraulic position Servo System for Precision Improvement

2014 ◽  
Author(s):  
Lihua Liang ◽  
Mingxiao Sun ◽  
Songtao Zhang ◽  
Yu Wen ◽  
Peng` Zhao ◽  
...  
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Servo System ◽  
Position Servo ◽  
Control Application ◽  
Neural Network Pid

Study on RBF Neural Network PID Control for Hydro-Viscous Drive System

2013 ◽  
Vol 470 ◽  
pp. 668-672
Author(s):  
Qing Rui Meng ◽  
Kai Wang ◽  
Dao Ming Wang ◽  
Jian Wang ◽  
Bao Cheng Song ◽  
...  
Keyword(s):  
Neural Network ◽  
Error Rate ◽  
Control Strategy ◽  
Pid Control ◽  
Rbf Neural Network ◽  
Drive System ◽  
Output Curve ◽  
Strategy Selection ◽  
Neural Network Pid ◽  
Selection Of

To verify the applicability of RBF neural network PID control on speed regulating start control for hydro-viscous drive system, analyze the principle of RBF neural network PID control, the simulation model is established based on SIMULINK and the control characteristics are analyzed based on the AMESim/MATLAB co-simulation. The results show that RBF neural network PID control has a good self-correcting effect on speed regulating start of hydro-viscous; it can make right judgments according to the error and error rate and adjust the output speed towards opposite direction of error; meanwhile, it ensures the smoothness of output curve and avoids excessive mechanical impact. The results play a guiding role for control strategy selection of speed regulating start.

Double Closed-Loop Controller Design of Brushless DC Torque Motor Based on RBF Neural Network

2012 ◽  
Vol 503-504 ◽  
pp. 1351-1356
Author(s):  
Deng Hua Li ◽  
Zhan Xian Chen ◽  
Shuang Zhai
Keyword(s):  
Neural Network ◽  
Closed Loop ◽  
Controller Design ◽  
Rbf Neural Network ◽  
Servo System ◽  
Brushless Dc ◽  
Pid Algorithm ◽  
Feed Forward Control ◽  
Motor Controller ◽  
Position Servo

For the problem of that the traditional brushless DC torque motor controller position servo system is difficult to track accurately the complex and varied location information, an improved double closed-loop controller is designed in this paper. A self-adaptive PID algorithm based on RBF neural network is employed to design position loop controller and a feed-forward control algorithm is used in the speed loop controller. The improved double closed-loop controller validated the feasibility of the new method for the design of brushless DC torque motor position servo system

scholarly journals Fault Diagnosis in a Hydraulic Position Servo System Using RBF Neural Network

2006 ◽  
Vol 19 (4) ◽  
pp. 346-353 ◽  
Author(s):  
Hong-mei LIU ◽  
Shao-ping WANG ◽  
Ping-chao OUYANG
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Rbf Neural Network ◽  
Servo System ◽  
Position Servo
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