Comparison of Fuzzy and Neural Systems for Implementation of Nonlinear Control Surfaces
In this paper, a comparison between different fuzzy and neural systems is presented. Instead of using traditional membership functions, such as triangular, trapezoidal and Gaussian, in fuzzy systems, the monotonic pair-wire or sigmoidal activation function is used for each neuron. Based on the concept of area selection, the neural systems can be designed to implement the identical properties like fuzzy systems have. All parameters of the proposed neural architecture are directly obtained from the specified design and no training process is required. Comparing with traditional neuro-fuzzy systems, the proposed neural architecture is more flexible and simplifies the design process by removing division/normalization units.
KeywordsMembership Function Fuzzy System Fuzzy Rule Neural System Fuzzy Variable
Unable to display preview. Download preview PDF.
- [Farrell and Polycarpou 2008]
- [Mamdani 1974]Mamdani, E.H.: Application of fuzzy algorithms for control of simple dynamic plant. IEEE Proceedings 121(12), 1585–1588 (1974)Google Scholar
- [Masuoka et al 1990]Masuoka, R., Watanabe, N., Kawamura, A., et al.: Neurofuzzy system-fuzzy inference using a structured neural network. In: Proc. of the Int. Conf. on Fuzzy Logic & Neural Networks, Hzuka, Japan, pp. 173–177 (1990)Google Scholar
- [McKenna and Wilamowski 2001]McKenna, M., Wilamowski, B.M.: Implementing a fuzzy system on a field programmable gate array. In: Int Joint Conf. on Neural Networks, Washington DC, pp. 189–194 (2001)Google Scholar
- [Narendra and Parthasarathy]
- [Takagi and Sugeno 1985]
- [Wilamowski 2002]Wilamowski, B.M.: Neural networks and fuzzy systems. In: Bishop, R.R. (ed.) Mechatronics Handbook, vol. 33(1), pp. 32–26. CRC Press, Boca Raton (2002)Google Scholar
- [Wilamowski and Binfet 1999]Wilamowski, B.M., Binfet, J.: Do fuzzy controllers have advantages over neural controllers in microprocessor implementation. In: Proc. of 2nd Conf. on Recent Advances in Mechatronics, Istanbul, Turkey, pp. 342–347 (1999)Google Scholar
- [Wilamowski and Binfet 2001]Wilamowski, B.M., Binfet, J.: Microprocessor Implementation of fuzzy systems and neural networks. In: Int. Joint Conf. on Neural Networks, Washington DC, pp. 234–239 (2001)Google Scholar
- [Wilamowski and Yu 2010]
- [Xie et al 2010]Xie, T.T., Yu, H., Wilamowski, B.M.: Replacing fuzzy systems with neural networks. In: Proc. IEEE Conf. on Human System Interaction, Rzeszow, Poland, pp. 189–193 (2010)Google Scholar
- [Yu and Wilamowski 2009]Yu, H., Wilamowski, B.M.: Efficient and reliable training of neural networks. In: Proc. 2nd IEEE Human System Interaction, Catania, Italy, pp. 109–115 (2009)Google Scholar