A new fuzzy identification method for unknown nonlinear discrete systems is presented by introducing adaptive critic designs into the generalized fuzzy hyperbolic model (GFHM). This method minimizes the long-time error other than the immediate error to improve the identification effect. We first represent the GFHM with a neural network structure, and then utilize the adaptive critic designs (ACDs) to get the optimal parameters of the network so that the long-time identification error is minimized. Finally, we give a simulation example to verify the effectiveness of this identification method. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Zhang, H., Luo, Y., & Liu, D. (2006). A new fuzzy identification method based on adaptive critic designs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3971 LNCS, pp. 804–809). Springer Verlag. https://doi.org/10.1007/11759966_118
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