The Design of Predictive Fuzzy-PID Controller in Temperature Control System of Electrical Heating Furnace

2010 ◽  
pp. 259-265 ◽  
Author(s):  
Ying-hong Duan
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Pid Controller ◽  
Heating Furnace ◽  
Electrical Heating ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

Application of a New Smith Fuzzy PID in Electric Boiler Temperature Control System

2015 ◽  
Vol 727-728 ◽  
pp. 633-636 ◽  
Author(s):  
Qiang Gu ◽  
Feng Long Zheng ◽  
Bin Bin Liu ◽  
Wen Yan Yang
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Pid Control ◽  
Pid Controller ◽  
Temperature Control System ◽  
Model Parameters ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Electric Boiler

Since the object model is time-varying and time-delay in the electric boiler temperature control system, Smith Fuzzy PID controller is applied in it. Simulation results in the paper show that the overshoot is reduced by 31.3% compared with the system under Smith PID control and the adjusting time reached a 30% reduction compared with those under Fuzzy PID control with T=380 and τ=110. In order to eliminate the oscillation problem in system when model parameters change, a new Smith Fuzzy PID controller with two degrees of freedom is applied, whose control performance is much better than that of Smith Fuzzy PID.

The Design and Simulation of Control System for Electrical Heating

2013 ◽  
Vol 325-326 ◽  
pp. 1193-1196
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Electrical Heating ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Fuzzy Pid Controller ◽  
Electric Boiler

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.

Multiple Models Fuzzy PID Controller Design in Air-Condition Temperature Control System

2013 ◽  
Vol 860-863 ◽  
pp. 1616-1619
Author(s):  
Hang Jiang ◽  
Xin Wang ◽  
Yi Hui Zheng ◽  
Li Xue Li ◽  
Yan Liu
Keyword(s):  
Temperature Control ◽  
Pid Control ◽  
Pid Controller ◽  
Controller Design ◽  
Temperature Control System ◽  
Multiple Models ◽  
Multiple Model ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller

This paper deals with the study of air-condition temperature control, which is a complex system of time varying, nonlinear, imprecise model and uncertain work environment. In this paper, a multiple models fuzzy PID controller is designed. Considering the air-condition temperature adjustment system to combat aircraft and the frequently changing external environment the multiple fuzzy PID controllers are estimated according to the temperature changing area. Each time, based on temperature tested, only one fuzzy PID Controller is chosen to improve the control precision. At the end, simulation results show that multiple model fuzzy PID control is superior to the single fuzzy PID control, which effectively improve the transient response of the system, the steady state accuracy and robustness, having good prospects for engineering applications.

Particle Swarm Optimization of PIλDμ Control of Heating Furnace Temperature Control System

2014 ◽  
Vol 721 ◽  
pp. 205-209
Author(s):  
Pei Guang Wang ◽  
Lian Zhang ◽  
Xiao Ping Zong
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Fractional Order ◽  
Temperature Control ◽  
Pid Controller ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Heating Furnace ◽  
Temperature Control System ◽  
Swarm Optimization

Due to the complexity of the heat transfer for heating furnace, some characteristics are caused such as big inertia, great lag. In the temperature control system for heating furnace, the traditional PID controller can not get satisfactory effect, that dynamic is instability and control accuracy is bad, which is very detrimental to the system to achieve optimum efficiency. A fractional order PIλDμ controller based on particle swarm optimization method was designed, at the same time compared with PID control. Simulation results show that, fractional order PIλDμ control based on particle swarm optimization has better convergence stability, faster response times and higher accuracy value. Fractional order PIλDμ controller has better dynamic performance, compared with traditional PID controller, greatly improves the quality control system.

Fuzzy Adaptive PID Controller Optimization Design in Temperature Control System

2014 ◽  
Vol 989-994 ◽  
pp. 3157-3160
Author(s):  
Xiao Peng Li ◽  
Lan Zhen Chen
Keyword(s):  
Control System ◽  
Transfer Function ◽  
Control Systems ◽  
Temperature Control ◽  
Pid Controller ◽  
Optimization Design ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Significant Performance ◽  
Fuzzy Adaptive

A new self-adjusting PID controller based fuzzy inferences is proposed. Using fuzzy inferences method, the PID parameters can be adjusted adaptively online for the varying state of the system. This approach has more significant performance and robustness than conventional PID contorllers in any conditions. Traditional fuzzy control systems have difficulties for plants with great delay.A fuzzy PID system based on the Smith compensation theorem is proposed in the paper.It allows to change the transfer function of the plant.Simulation results are also given.

The Application and Simulation Research of the Fuzzy PID Control Used in PVC Polymerization Temperature Control System

2012 ◽  
Vol 466-467 ◽  
pp. 47-51 ◽  
Author(s):  
Jing Liu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Temperature Control System ◽  
Polymerization Temperature ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Simulation Research ◽  
Fuzzy Pid Controller ◽  
On Line

The process of PVC polymerization is nonlinear and time-delayed. It is very difficult to establish an exact mathematical model. Based on the analysis of the conventional PID controller’s limitation, the fuzzy PID control system of PVC polymerization is introduced. A new kind of fuzzy PID controller is designed and the three parameters of PID can be self-tuned on-line. The simulation result proves that fuzzy PID controller is better than common PID controller.

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