Abstract
The environment of room temperature is complicated and it is difficult to get precise mathematics model for the control of air-condition with frequency change. It is difficult using conventional fuzzy control way to control air-condition to get better control performance. Fuzzy neural network has strong fuzzy reasoning ability and learning ability, which can control air-condition with frequency change to get better control effect. In this paper, an improved fuzzy neural network controller is designed to control air-condition. In order to overcome the weakness of slow learning speed for fuzzy neural network, GAs is employed to optimize parameters of fuzzy neural network. In order to improve training speed and overcome the shortcoming of local optimization, the designed genetic algorithm is improved based on the control system. Simulating experiment shows that the designed controller has better controlling effect than other conventional fuzzy controller.
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© 2009 Springer-Verlag Berlin Heidelberg
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Wang, S., Zhang, Z., Xiao, Z., Yuan, X. (2009). A Study on Improved Fuzzy Neural Network Controller for Air-Condition with Frequency Change. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_17
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DOI: https://doi.org/10.1007/978-3-642-01510-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01509-0
Online ISBN: 978-3-642-01510-6
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