scholarly journals The Applications of Fuzzy Neural Network Used in Network Center Room Temperature Control

2013 ◽  
Vol 02 (01) ◽  
pp. 43-47
Author(s):  
浩 牟
Keyword(s):  
Neural Network ◽  
Temperature Control ◽  
Room Temperature ◽  
Fuzzy Neural Network ◽  
Fuzzy Neural

Temperature Control of Batch Reaction Based on Genetic Fuzzy Neural Network

2011 ◽  
Vol 204-210 ◽  
pp. 1968-1971 ◽  
Author(s):  
Chun Tao Man ◽  
Jia Cui ◽  
Xin Xin Yang ◽  
Jun Kai Wang ◽  
Tian Feng Wang
Keyword(s):  
Neural Network ◽  
Temperature Control ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Design Method ◽  
Batch Reactor ◽  
Batch Processes ◽  
Strong Nonlinearity ◽  
Control Scheme ◽  
Fuzzy Neural

The batch reactor has strong nonlinearity and hysteresis, the conventional control method is hard to meet the control requirements. According to the batch processes temperature control, this thesis proposed an intelligent control scheme. Combined neural networks with fuzzy logic control, searching and optimized parameters of fuzzy neural network by using Genetic Algorithm (GA), displayed the design method and optimization steps, and the simulation results verify the control scheme which proposed is feasible and effective.

Design of Temperature Control System Based on DSP and Fuzzy Neural Network

2013 ◽  
Vol 823 ◽  
pp. 384-387
Author(s):  
Ya Juan Chen ◽  
Yue Hong Zhang ◽  
Gen Wang Ying
Keyword(s):  
Neural Network ◽  
Control System ◽  
Temperature Control ◽  
Fuzzy Neural Network ◽  
Good Control ◽  
Temperature Control System ◽  
Control Effect ◽  
Fuzzy Neural ◽  
Electric Boiler ◽  
Self Tuning

Using fuzzy neural network to tune PID parameters, and DSP as processor, it was designed that a set of electric boiler temperature control system based on PID parameters self-tuning, including the design of each hardware module and each software subroutine of the system. Experimental results show that compared with the traditional PID temperature control system, this temperature control system has the advantages such as good control effect, easy parameter adjustment, strong anti-jamming capability, better adaptability and robustness, has the feasibility and practical value.

The Application Research of PLC Temperature Control System Based on Fuzzy Neural Network PID

2013 ◽  
Vol 340 ◽  
pp. 517-522
Author(s):  
Yong Wei Lu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Temperature Control ◽  
Control Algorithm ◽  
Fuzzy Neural Network ◽  
Experimental Result ◽  
Temperature Control System ◽  
Pid Algorithm ◽  
Fuzzy Neural ◽  
Neural Network Pid

it is hard to establish the accurate model by using the traditional PID algorithm, and hard to adjust the system parameter in nonlinear system. In order to solve this problem, this paper proposed PID algorithm based on Fuzzy Neural Network. This algorithm combined PID algorithm, fuzzy control algorithm and neural network algorithm together, and formed one kind intelligent control algorithm. This paper designed and researched this algorithm, and applied in the PLC temperature control system. The experimental result indicated that the fuzzy neural network PID controller improved the controller quality, conquered some question such as variable parameter and nonlinear, and enhanced the systems robustness.

Fuzzy Neural Network Based on Genetic Algorithm for Temperature Control of Variable Air Volume Air Conditioning

2014 ◽  
Vol 599-601 ◽  
pp. 952-955
Author(s):  
Jie Jia Li ◽  
Yong Qiang Chen ◽  
Xiao Yan Han
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Air Conditioning ◽  
Fuzzy Neural Network ◽  
Learning Ability ◽  
Variable Air Volume ◽  
Air Volume ◽  
Fuzzy Neural

In this paper, the theory of the fuzzy control and self-learning ability of neural network is combined, joining the genetic algorithm to optimize the fuzzy control rules, so in the light of temperature control system of variable air volume air conditioning puts forward a fuzzy neural network control method based on genetic algorithm,and this paper introduces in detail the structure, algorithm of fuzzy control and neural network. In addition,this paper verifies the superiority of the fuzzy neural network based on genetic algorithm and ordinary fuzzy neural control.

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