A Theoretical Foundation of Goal Representation Heuristic Dynamic Programming

Goal representation heuristic dynamic programming (GrHDP) control design has been developed in recent years. The control performance of this design has been demonstrated in several case studies, and also showed applicable to industrial-scale complex control problems. In this paper, we develop the th...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems Vol. 27; no. 12; pp. 2513 - 2525
Main Authors: Zhong, Xiangnan, Ni, Zhen, He, Haibo
Format: Journal Article
Language:English
Published: United States IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:2162-237X, 2162-2388
Online Access:Get full text
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Summary:Goal representation heuristic dynamic programming (GrHDP) control design has been developed in recent years. The control performance of this design has been demonstrated in several case studies, and also showed applicable to industrial-scale complex control problems. In this paper, we develop the theoretical analysis for the GrHDP design under certain conditions. It has been shown that the internal reinforcement signal is a bounded signal and the performance index can converge to its optimal value monotonically. The existence of the admissible control is also proved. Although the GrHDP control method has been investigated in many areas before, to the best of our knowledge, this is the first study of presenting the theoretical foundation of the internal reinforcement signal and how such an internal reinforcement signal can provide effective information to improve the control performance. Numerous simulation studies are used to validate the theoretical analysis and also demonstrate the effectiveness of the GrHDP design.
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ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2015.2490698