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Second-Order Training of Adaptive Critics for Online Process Control

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Govindhasamy, James J., McLoone, Sean F. and Irwin, George W. (2005) Second-Order Training of Adaptive Critics for Online Process Control. IEEE Trans. Systems Man. and Cybernetics, Part B, 35 (2). pp. 381-385.

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Abstract

This paper deals with reinforcement lear ning for process modeling and control using a model-free, action- dependent adaptive critic (ADAC). A new modified recursive Levenberg Marquardt (RLM) training algorithm, called temporal difference RLM, is developed to improve the ADAC performance. Novel application results for a simulated continuously-stirred-tank-reactor process are included to show the superiority of the new algorithm to conventional temporal-difference stochastic backpropagation.

Item Type:	Article
Additional Information:	Copyright © 2005 IEEE.   Reprinted from  (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of NUI Maynooth ePrints and eTheses Archive's products or services.  Internal or personal use of this material is permitted.  However, permission for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. copyright laws protecting it.
Keywords:	Action- dependent Adaptive Critic, Levenberg Marquardt, Online process control
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	683
Depositing User:	Sean McLoone
Date Deposited:	23 Sep 2008
Journal or Publication Title:	IEEE Trans. Systems Man. and Cybernetics, Part B
Publisher:	Institute of Electrical and Electronics Engineers
Refereed:	Yes
URI:	https://mural.maynoothuniversity.ie/id/eprint/683
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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