Electrical Heating Reactor Control System Using Neural Network and the Fuzzy Controller

Author(s):  
E. Muravyova ◽  
I. Almakaev
2013 ◽  
Vol 325-326 ◽  
pp. 1193-1196
Author(s):  
Guo Sheng Xu

In view of the fact that the performance of any conventional PID control can t meet the requirement an electric boiler temperature control system, this paper puts forward a kind of improved algorithm for tuning the PID parameters. an adaptive fuzzy controller with adjusting factor is proposed in this paper. Experimental results illustrate that the adaptive fuzzy PID controller achieved the system performance index. The method of adaptive fuzzy PID control is a ideal method.


1989 ◽  
Vol 28 (3) ◽  
pp. 9-15 ◽  
Author(s):  
Victor C. Lim ◽  
Roger M. Ray

2021 ◽  
Vol 40 (1) ◽  
pp. 65-76
Author(s):  
Peng Zhou ◽  
Junxing Tian ◽  
Jian Sun ◽  
Jinmei Yao ◽  
Defang Zou ◽  
...  

According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. The fuzzy neural network predictive control technology can be used to control the tool hydraulic system of Tunnel Boring Machine.


Sign in / Sign up

Export Citation Format

Share Document