Abstract
A new fuzzy neural network is introduced in this paper which employs self-organization competition neural network to optimize the structure of the fuzzy neural network, and applies a genetic algorithm to adjust the connection weights of the fuzzy neural network so as to get the best structure and weights of the fuzzy neural network. Simulations are made when the pole becomes 2 meters and the random white noise is added in the cart-pendulum system, and control effects of the Adaptive Neural Fuzzy Illation System (ANFIS) and Genetic Algorithm Fuzzy Neural Network (GAFNN) are analyzed. Simulation results indicate that GAFNN controller has greater control performance, high convergence speed, strong robustness and better dynamic characteristics. The effectiveness of the method introduced in this paper is demonstrated by its encouraging study results.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
FengJuang, C.: A TSK-Type Recurrent Fuzzy Network for Dynamic Systems Processing by Neural Network and Genetic Algorithms. IEEE Transactions on Fuzzy Systems 10(2) (2002)
Renhou, L.: The Intelligent Control Theories and methods. Electronics science and technology university of Xian (1999)
Hsiung Hung, T., Ming-Feng, Y., Hung-Ching, L.: A pi-link fuzzy controller implementation for the inverted pendulum system. In: Processing of IEEE Conference on Intelligent Processing System, pp. 218–222. IEEE Computer Society Press, Los Alamitos (1997)
Mario, E.M., Holzapfel, F.: Fuzzy-logic control of an inverted pendulum with vision feedback. IEEE Trans. on Education 14(2), 165–170 (1998)
Miyamoto, M., Kawato, M., Setoyama, T., Suzuki, R.: Feedback Error Learning. IEEE Trans. on Neural Networks 1, 251–265 (1998)
Sigeru, Omatu, T.F., Michifumi, Y.: Neuro-pid Control for Inverted Single and Double Pendulums. In: IEEE Conference, pp. 2685–2690. IEEE Computer Society Press, Los Alamitos (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dong, X., Wang, H., Xu, Q., Zhao, X. (2007). Research on Applications of a New-Type Fuzzy-Neural Network Controller. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_72
Download citation
DOI: https://doi.org/10.1007/978-3-540-74769-7_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74768-0
Online ISBN: 978-3-540-74769-7
eBook Packages: Computer ScienceComputer Science (R0)