Qualitative Models for Adaptive Critic Neurocontrol
Published In
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Document Type
Citation
Publication Date
12-1-1999
Abstract
We demonstrate the use of qualitative models in the DHP method of training neurocontrollers. Two Fuzzy approaches to developing qualitative models are explored: a priori application of problem specific knowledge, and estimation of a first order TSK Fuzzy model. These approaches are demonstrated respectively on the cart-pole system and a non-linear multiple-input-multiple-output plant proposed by Narendra. In both cases we find that a simplified model based on a Fuzzy framework enables better performance to be obtained as compared to use of non-Fuzzy models of equivalent complexity. In both cases we use models that, while poor as one-step predictors, achieve effectiveness in the DHP training context equivalent to that exact analytic models.
Locate the Document
https://doi.org/10.1109.ICSMC.1999.814134
DOI
10.1109/ICSMC.1999.814134
Persistent Identifier
https://archives.pdx.edu/ds/psu/37321
Citation Details
Shannon, T. T., & Lendaris, G. G. (1999, October). Qualitative models for adaptive critic neurocontrol. In IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 99CH37028) (Vol. 1, pp. 455-460). IEEE.