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Neuro-fuzzy Controller Theory and Application

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Intelligent Control Systems with LabVIEW™

Abstract

Fuzzy systems allow us to transfer the vague fuzzy form of human reasoning to mathematical systems. The use of IF–THEN rules in fuzzy systems gives us the possibility of easily understanding the information modeled by the system. In most of the fuzzy systems the knowledge is obtained from human experts. However this method of information acquisition has a great disadvantage given that not every human expert can and/or want to share their knowledge.

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Bibliography

References

  1. Ponce P, et al. (2007) Neuro-fuzzy controller using LabVIEW. Proceedings of 10th ISC Conference, IASTED, Cambridge, MA, 19–21 Nov 2007

    Google Scholar 

  2. Takagi T, Sugeno M (1998) Fuzzy identification of systems and its application to modeling and control. IEEE Trans Syst Man Cyber 15:116–132

    Google Scholar 

  3. Fourier J (2003) The analytical theory of heat. Dover, Mineola, NY

    Google Scholar 

  4. Ponce P, et al. (2006) A novel neuro-fuzzy controller based on both trigonometric series and fuzzy clusters. Proceedings of IEEE International Conference on Industrial Technology, India, 15–17 Dec 2006

    Google Scholar 

  5. Kanjilal PP (1995) Adaptive prediction and predictive control. Short Run, Exeter, UK

    MATH  Google Scholar 

  6. Ramirez-Figueroa FD, Mendez-Cisneros D (2007) Neuro-fuzzy navigation system for mobile robots. Dissertation, Electronics and Communications Engineering, Tecnológico de Monterrey, México, May 22 2007

    Google Scholar 

  7. Images Scientific Instrumentation (2009) http://www.imagesco.com. Accessed on 22 Feb 2009

    Google Scholar 

  8. Jang J-SR (1993) ANFIS: adaptive network-based inference system. IEEE Trans Syst Man Cyber 23(3): 665–685

    Article  MathSciNet  Google Scholar 

  9. Jang J-SR, Sun C-T, Mizutani E (1997) Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice Hall, New York

    Google Scholar 

  10. ITESM-CCM Team (2009) Electric wheelchair presented in NIWEEK 2009 Austin Texas

    Google Scholar 

Further Reading

  • Jang JSR (1992) Self-Learning Fuzzy Controller Based on Temporal Back-Propagation. IEEE Trans. on Neural Networks, 3:714–723

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  • Jang JSR (1993) ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Trans. on Systems, Man, and Cybernetics, 23:665–685

    Article  Google Scholar 

  • Jang JSR, Sun CT (1993) Functional Equivalence Between Radial Basis Function Networks and Fuzzy Inference Systems. IEEE Trans. on Neural Networks, 4:156–159

    Article  Google Scholar 

  • Jang JSR, Sun CT (1995) Neuro-Fuzzy Modeling and Control. The Proceedings of the IEEE, 83:378–406a

    Article  Google Scholar 

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© 2010 Springer-Verlag London Limited

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(2010). Neuro-fuzzy Controller Theory and Application. In: Intelligent Control Systems with LabVIEW™. Springer, London. https://doi.org/10.1007/978-1-84882-684-7_4

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  • DOI: https://doi.org/10.1007/978-1-84882-684-7_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-683-0

  • Online ISBN: 978-1-84882-684-7

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