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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Vydáno v:IEEE transaction on neural networks and learning systems Ročník 27; číslo 12; s. 2513 - 2525
Hlavní autoři: Zhong, Xiangnan, Ni, Zhen, He, Haibo
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptive dynamic programming (ADP)
Algorithm design and analysis
Approximation algorithms
Control methods
Convergence
convergence analysis
Design
Dynamic programming
Goal programming
goal representation
Heuristic
Mathematical model
neural network
online learning and control
Performance analysis
Performance indices
Problem solving
Reinforcement
Representations
Theoretical analysis
Upper bound
ISSN:2162-237X, 2162-2388
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Shrnutí: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