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Single neuron control based on genetic algorithm and its application

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2 Author(s)
Fang Ding ; Department of Aeronautic Automation, Civil Aviation University of China, TianJin 300300, China ; Lili Zhang

Focusing on the problem that the PID parameters is hard to confirm and its ability to adapt to external disturbances is poor, and the single neuron controller in practical applications is difficult to determine the weight and so on, apply genetic algorithms which has optimization searching ability to single neuron control theory, design a controller which uses genetic algorithms to train the weights of the single neuron controller and its threshold values, which is said that through the adjustment of the genetic algorithm repeatedly to find out the best weights of the single neuron controller, with the result that the problem has the optimal solution. Use MATLAB to simulate the controller and the result shows that it has good stability and strong ability to adapt to the changing environment.

Published in:

Computing, Control and Industrial Engineering (CCIE), 2011 IEEE 2nd International Conference on  (Volume:1 )

Date of Conference:

20-21 Aug. 2011