A new pseudo-Gaussian-based recurrent fuzzy CMAC model for dynamic systems processing

Authors:
D. -Y. Wang;C. -J. Lin;C. -Y. Lee
Affiliations:
Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taiwan, R.O.C.;Department of Electrical Engineering, National University of Kaohsiung, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Nankai Institute of Technology, Taiwan, R.O.C.
Venue:
International Journal of Systems Science
Year:
2008

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Abstract

This article presents a new pseudo-Gaussian-based recurrent fuzzy cerebellar model articulation controller (PG-RFCMAC) model for identifying various nonlinear dynamic systems. A pseudo-Gaussian basis function can provide the self-organising PG-RFCMAC model, which own a higher flexibility and can approach the optimise result more accurately. The pseudo-Gaussian basis function is used to model the hypercube cells and the fuzzy weights. The recurrent network is embedded in the PG-RFCMAC model by adding feedback connections with a receptive field cell, where the feedback units act as memory elements. An on-line learning algorithm is proposed for the automatic construction of the proposed model during the learning procedure. Computer simulations were conducted to illustrate the performance and applicability of the proposed model.