Skip to main content

A Study on Improved Fuzzy Neural Network Controller for Air-Condition with Frequency Change

  • Conference paper
Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Included in the following conference series:

  • 1344 Accesses

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Van, A.J., Der, W.A.L.: Application of Fuzzy Logic Control in Industry. Fuzzy Sets and Systems 74, 33–41 (1995)

    Article  Google Scholar 

  2. Cheng, C.B.: Fuzzy Process Control: Construction of Control Charts with Fuzzy Numbers. Fuzzy Sets and Systems 154, 287–303 (2005)

    Article  MathSciNet  Google Scholar 

  3. Fenga, G., Caoa, S.G., Reesb, N.W.: Stable Adaptive Control of Fuzzy Dynamic Systems. Fuzzy Sets and Systems 131, 217–224 (2002)

    Article  MathSciNet  Google Scholar 

  4. Sun, Q., Li, R.E., Zhang, P.A.: Stable and Optimal Adaptive Fuzzy Control of Complex Systems Using Fuzzy Dynamic Model. Fuzzy Sets and Systems 133, 1–17 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  5. Juuso, E.K.: Integration of Intelligent Systems in Development of Smart Adaptive Systems. International Journal of Approximate Reasoning 35, 307–337 (2004)

    Article  MATH  Google Scholar 

  6. Pham, D.T., Karaboga, D.: Self-tuning Fuzzy Controller Design Using Genetic Optimisation and Neural Network Modeling. Artificial Intelligence in Engineering 13, 119–130 (1999)

    Article  Google Scholar 

  7. Juuso, E.K.: Integration of Intelligent Systems in Development of Smart Adaptive Systems. International Journal of Approximate Reasoning 35, 307–337 (2004)

    Article  MATH  Google Scholar 

  8. Ahtiwash, O.M., Abdulmin, M.Z., Siraj, S.F.: A Neural-Fuzzy Logic Approach for Modeling and Control of Nonlinear Systems. International symposium on intelligent Control Vancouver 1, 270–275 (2002)

    Article  Google Scholar 

  9. Oh, S.K., Pedrycz, W., Park, B.J.: Self-organizing Neuro Fuzzy Networks in Modeling Software Data. Fuzzy Sets and Systems 145(3), 165–181 (2004)

    Article  MathSciNet  Google Scholar 

  10. Aliev, R.K.A., Fazlollahi, B., Vahidov, R.M.: Genetic Algorithm-based Learning of Fuzzy Neural Networks. Part 1: feed-forward fuzzy neural networks. Fuzzy Sets and Systems 118, 351–358 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  11. Lin, C.J.: A GA-based Neural Fuzzy System for Temperature Control. Fuzzy Sets and Systems 143, 311–333 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  12. Angelov, P.: An Approach for Fuzzy Rule-base Adaptation Using On-line Clustering. International Journal of Approximate Reasoning 35, 275–289 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  13. Gao, Y., Meng, J.: Modelling Control and Stability Analysis of Nonlinear Systems Using Generalized FNN. International Journal of Systems Science 34(6), 427–438 (2003)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

  • 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

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics