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Vol. 153, No. 6, June 2013, pp. 100-104

 

Bullet

 

Application and Simulation of Fuzzy Neural Network PID Controller in the Aircraft Cabin Temperature
 
Ding Fang, Feng Na

Department of Aeronautic Automation, Civil Aviation University of China, Tianjin, 300300, China

Tel.: (086)18602615819

E-mail: dingfang_60@163.com, fengna6868@126.com

 

Received: 3 May 2013   /Accepted: 14 June 2013   /Published: 25 June 2013

Digital Sensors and Sensor Sysstems

 

Abstract: Considering complex factors of affecting ambient temperature in Aircraft cabin, and some shortages of traditional PID control like the parameters difficult to be tuned and control ineffective, this paper puts forward the intelligent PID algorithm that makes fuzzy logic method and neural network together, scheming out the fuzzy neural net PID controller. After the correction of the fuzzy inference and dynamic learning of neural network, PID parameters of the controller get the optimal parameters. MATLAB simulation results of the cabin temperature control model show that the performance of the fuzzy neural network PID controller has been greatly improved, with faster response, smaller overshoot and better adaptability.

 

Keywords: PID, Fuzzy control, Neural net, Cabin temperature.

 

 

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