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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| Published in | Sensors & transducers Vol. 153; no. 6; p. 100 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Toronto
IFSA Publishing, S.L
01.06.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2306-8515 1726-5479 |
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| 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. |
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| AbstractList | 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. |
| Author | Fang, Ding Na, Feng |
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| Snippet | Considering complex factors of affecting ambient temperature in Aircraft cabin and some shortages of traditional PID control like the parameters difficult to... |
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| SubjectTerms | Artificial neural networks Cabins Computer simulation Control algorithms Controllers Fuzzy logic Fuzzy sets Mathematical models Matlab Neural networks Neurons Proportional integral derivative Simulation Temperature |
| Title | Application and Simulation of Fuzzy Neural Network PID Controller in the Aircraft Cabin Temperature |
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