COMPARATIVE STUDY OF FUZZY CONTROL, PID CONTROL, AND ADVANCED FUZZY CONTROL FOR SIMULATING A NUCLEAR REACTOR OPERATION

2000 ◽  
Vol 29 (2) ◽  
pp. 263-279 ◽  
Author(s):  
XIAOZHONG LI ◽  
DA RUAN
2013 ◽  
Vol 380-384 ◽  
pp. 294-297 ◽  
Author(s):  
Xin Wei Li

A temperature rising control system and temperature maintaining control system were designed in according to time-variable and hysteretic nature of temperature change and limitation when traditional PID control deals with nonlinear systems. A new type of intelligent fuzzy controller combination of traditional PID control and fuzzy control was designed and applied in temperature maintaining control system. The simulation results show that the holding phase at elevated temperatures and temperature, the temperature curve has a high steady-state accuracy and dynamic performance in the period of temperature rising and maintaining, and the system and controller cause a better result.


2012 ◽  
Vol 217-219 ◽  
pp. 2463-2466 ◽  
Author(s):  
Xue Gang Hou ◽  
Cheng Long Wang

Induction heating furnace temperature control is a complex nonlinear hysteretic inertial process, it's difficult to obtain an accurate mathematical model because the temperature and disturb from outside is complicated. The normal PID control algorithm is hard to satisfy the standards of control. The fuzzy PID controller provided in this article is a combination between fuzzy control and the traditional PID control. The Fuzzy control theory is used to setting the ratio, the integral and the differential coefficient of the PID control. In the run-up stage, rapidity is guaranteed, overstrike and the steady-state error is up to the mustard. An example indicates that fuzzy PID control is superior to the normal PID controller.


2013 ◽  
Vol 816-817 ◽  
pp. 857-861
Author(s):  
You Jun Yue ◽  
Yue Xu ◽  
Hui Zhao ◽  
Hong Jun Wang

When wind turbine works under rated wind speed, we often use fuzzy controller to control rotate speed and keep the best sharp blade speed to achieve the aim of capture the largest wind power. Due to the nonlinearity of wind power, the uncertainty of timely change and other factors, though fuzzy PID control is the combination of fuzzy control and PID control, which can solve the problem of nonlinear very well, it focuses only on the fuzziness, and fails to consider the random error brought by wind speed change. Therefore this paper designed fuzzy reasoning PID controller based on cloud model on the base of analyzing parameters of wind power and advantage as well as shortage of both PID control and fuzzy control. Then start the RT-LAB simulation platform. The simulation result proved that this method can effectively depress the overshoot. And its stability and dynamic speed response is better than PID control and fuzzy control. It achieved ideal result.


2014 ◽  
Vol 886 ◽  
pp. 369-373 ◽  
Author(s):  
Chun Juan Han ◽  
Fa Cheng Rui

PID control (fuzzy control) is one of the earliest and most widely used control laws in process control applications. It can obtain satisfactory control results for most industrial objects. People use PID control (or PI, PD control) in a variety of controllers in frequency control system. However, with the rapid development of modern large-scale industry, and the degree of automation is getting higher and higher, the scope of applications in frequency control technology has been continuously expanding, while it has wider and deeper requirements for the performance of speed control system. AC drive system has uncertain factors, such as the existing parameter variability, load disturbance, nonlinear and strong coupling in under controlled AC motors, they will seriously affect the performance of speed control system. The traditional PID control seems a little powerless. The fuzzy control is a nonlinear control in essence, it can significantly improve the robustness of the system comparing to linear PI controller, and it can more effectively overcome various nonlinear factors in transmission system. For a multi-loop speed control system, the outer loop is the fundamental factor in determining the system performance. Inner loop is mainly for changing object properties in order to facilitate the controlling actions of the outer loop. The sampling frequency of inner loop is lower than the one in outer loop, which is facilitating for the realization of intelligent control.


JOM ◽  
2009 ◽  
Vol 61 (7) ◽  
pp. 24-27
Author(s):  
R. Szilard ◽  
P. Planchon ◽  
J. Busby

2014 ◽  
Vol 494-495 ◽  
pp. 1582-1586 ◽  
Author(s):  
Jun Liu ◽  
Qian Wei Xie

Focusing on the non-linear, time-varying, strong coupling and external load disturbance existing in PMLSM, a fuzzy PID controller based on genetic algorithms is designed to control the speed of PMLSM by absorbing the advantages of PID control and fuzzy control, and the genetic algorithm method is used to optimize fuzzy control rules. A simulation experiment was made to compare the effects of traditional PID control and fuzzy PID based on genetic algorithm control by Matlab. The simulation results verify that fuzzy PID control based on genetic algorithm is superior to PID control in dynamic stability performance and speed tracking power.


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