Study on the idity fuzzy neural network controller based on improved genetic algorithm of intelligent temperature control system in vegetable greenhouse

2009 ◽  
Author(s):  
Su Zhang ◽  
Hongbo Yuan ◽  
Yuhong Zhou ◽  
Nan Wang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Control System ◽  
Temperature Control ◽  
Fuzzy Neural Network ◽  
Temperature Control System ◽  
Improved Genetic Algorithm ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural

Fuzzy Neural Network Controller Based on Improved Genetic Algorithm for Temperature of Glass Tempering and Annealing Process

2010 ◽  
Vol 154-155 ◽  
pp. 214-219
Author(s):  
Xiao Kan Wang ◽  
Zhong Liang Sun ◽  
Sanci Guo ◽  
Chao Qun Shen
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fuzzy Neural Network ◽  
Annealing Process ◽  
Time Varying ◽  
Improved Genetic Algorithm ◽  
Neural Network Controller ◽  
Network Controller ◽  
Time Varying Parameters ◽  
Fuzzy Neural

The temperature control of the glass tempering and annealing process has characteristics of time-varying parameters，nonlinear and big lag. It is difficult to meet the expected control effect with the common control method. To solve this problem，this paper puts forward a kind of fuzzy neural network controller optimized by genetic algorithm. First，it uses neural network to construct fuzzy logic system according to the structure equivalence rule，thus the optimization of fuzzy control rules and membership functions can be realized by finding the weight value of the neural network. Then，it uses the improved genetic algorithm to find the global optimum weighted factors with a high speed so to improve the performance of the controller. The simulation results show that the optimized fuzzy neural network controller can obtain an excellent control performance for the nonlinearity system with time- varying parameters and lag.

Research on Intelligent Variable Frequency of Air-Conditioner Control System Based on Fuzzy Control

2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Neural Network ◽  
Air Conditioner ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Fuzzy Control Strategy

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.

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.

The Research and Application of the Fuzzy Neural Network Control Based on Genetic Algorithm

2011 ◽  
Vol 403-408 ◽  
pp. 191-195
Author(s):  
Yong Chao Zhang ◽  
Wen Zhuang Zhao ◽  
Jin Lian Chen
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fuzzy Neural Network ◽  
Network Control ◽  
Intelligent Control System ◽  
Neural Network Controller ◽  
Network Controller ◽  
Controller Performance ◽  
Fuzzy Neural ◽  
Neural Network Structure

How fuzzy technology and neural networks and genetic algorithm combine with each other has become the focus of research. A fuzzy neural network controller was proposed based on defuzzification and optimization around the fuzzy neural network structure. Genetic algorithm of fuzzy neural network was brought forward based on optimal control theory. Optimal structure and parameters of fuzzy neural network controller were Offline searched by way of controller performance indicators of genetic algorithm. Fuzzy neural network controller through genetic algorithm was accessed in fuzzy neural network intelligent control system.

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