Adaptive Dynamic Programming for Robust Regulation and Its Application to Power Systems

This paper presents a novel robust regulation method for a class of continuous-time nonlinear systems subject to unmatched perturbations. To begin with, the robust regulation problem is transformed into an optimal regulation problem by constructing a value function for the auxiliary system. Then, a...

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Veröffentlicht in:IEEE transactions on industrial electronics (1982) Jg. 65; H. 7; S. 5722 - 5732
Hauptverfasser: Yang, Xiong, He, Haibo, Zhong, Xiangnan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.07.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptive dynamic programming (ADP)
Adaptive systems
Algorithms
Computer simulation
Dynamic programming
Games
neural network
Nonlinear systems
Optimal control
Perturbation methods
reinforcement learning
Robust control
robust regulation
Robustness
System dynamics
unmatched perturbation
Weight
ISSN:0278-0046, 1557-9948
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Zusammenfassung:This paper presents a novel robust regulation method for a class of continuous-time nonlinear systems subject to unmatched perturbations. To begin with, the robust regulation problem is transformed into an optimal regulation problem by constructing a value function for the auxiliary system. Then, a simultaneous policy iteration (SPI) algorithm is developed to solve the optimal regulation problem within the framework of adaptive dynamic programming. To implement the SPI algorithm, actor and critic networks are employed to approximate the optimal control and the optimal value function, respectively, and the Monte Carlo integration method is applied to obtain the unknown weight parameters. Finally, two examples, including a power system, are provided to demonstrate the applicability of the developed approach.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2017.2782205