Title

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

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