Application and Simulation of Fuzzy Neural Network PID Controller in the Aircraft Cabin Temperature

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 toget...

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Bibliographic Details
Published inSensors & transducers Vol. 153; no. 6; p. 100
Main Authors Fang, Ding, Na, Feng
Format Journal Article
LanguageEnglish
Published Toronto IFSA Publishing, S.L 01.06.2013
Subjects
Artificial neural networks
Cabins
Computer simulation
Control algorithms
Controllers
Fuzzy logic
Fuzzy sets
Mathematical models
Matlab
Neural networks
Neurons
Proportional integral derivative
Simulation
Temperature
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ISSN2306-8515
1726-5479

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Summary: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.
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ISSN:2306-8515
1726-5479