DocumentCode :
2765694
Title :
Qualitative Adaptive Critics
Author :
Shannon, Thaddeus T.
Author_Institution :
Portland State Univ., Portland
fYear :
0
fDate :
0-0 0
Firstpage :
62
Lastpage :
67
Abstract :
In this paper we compare the use of qualitative adaptive critics to traditional quantitative critics for the design of control systems. Our approach uses a qualitative implementation of the Bellman recursion to train critic and controller networks. This extends previous work with univariate plants to multivariate plants with multiple control objectives. The results indicate that the superior control achieved by more sophisticated model based adaptive critic methods is due to qualitatively more accurate estimates of the gradient of the secondary utility function as opposed to increased numerical precision.
Keywords :
adaptive control; control system synthesis; multivariable control systems; adaptive critic methods; control system design; controller networks; multiple control objectives; qualitative adaptive critics; Adaptive control; Computational intelligence; Control systems; Dynamic programming; Feedback; Jacobian matrices; Laboratories; Optimal control; Programmable control; Supervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246660
Filename :
1716071
Link To Document :
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