A Theoretical Foundation of Goal Representation Heuristic Dynamic Programming
Document Type
Article
Date of Original Version
12-1-2016
Abstract
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.
Publication Title, e.g., Journal
IEEE Transactions on Neural Networks and Learning Systems
Volume
27
Issue
12
Citation/Publisher Attribution
Zhong, Xiangnan, Zhen Ni, and Haibo He. "A Theoretical Foundation of Goal Representation Heuristic Dynamic Programming." IEEE Transactions on Neural Networks and Learning Systems 27, 12 (2016): 2513-2525. doi: 10.1109/TNNLS.2015.2490698.