Application of a self-organizing fuzzy neural network controller with group-based genetic algorithm to greenhouse

2011 ◽  
Author(s):  
Yuan Yao ◽  
Kailong Zhang ◽  
Xingshe Zhou
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fuzzy Neural Network ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Self Organizing

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.

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.

Fuzzy Neural Network Controller Based on Hybrid GA-BP Algorithm

2013 ◽  
Vol 823 ◽  
pp. 335-339 ◽  
Author(s):  
Yin Ping Chen ◽  
Hong Xia Wu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fuzzy Neural Network ◽  
Random Search ◽  
Bp Algorithm ◽  
Neural Network Controller ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Initial States ◽  
Searching Ability

This paper presents a hybrid GA-BP algorithm for fuzzy neural network controller (FNNC). BP algorithm is a method to monitor learning, easily realized and with good local searching ability. But it depends too much on the the initial states of the network. Genetic algorithm is a random search algorithm which has strong global searching ability. The hybrid GA-BP algorithm ensure the global convergence of learning by genetic algorithm, overcomes the BP algorithms dependency on the initial states on the one hand. On the other hand, combined with the BP algorithm overcome the simple genetic algorithms randomness, improve the searching efficiency. The simulations on the inverted pendulun problem show good performance and robustness of the proposed fuzzy neural network controller based on hybrid GA-BP algorithm.

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.

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