Optimization of Train ATO System Based on RBF Neural Network PID Control

2020 ◽  
Author(s):  
Wei Wanpeng ◽  
Dong Yu
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Rbf Neural Network ◽  
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.

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.

Design of Ship Engine Speed System Based on RBF Neural Network PID Control

2021 ◽  
Author(s):  
Qing Wang ◽  
Zongquan Jiang ◽  
Yuanchang He ◽  
Lili Zhou ◽  
Li Geng
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Engine Speed ◽  
Rbf Neural Network ◽  
Neural Network Pid
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