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Study on Catenary Current Harmonic and Traction Characteristics of New Type Electric Multiple Unit Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Two-Objective Optimization Reinforcement Learning Used in Single-Phase Rectifier Control

Authors : Ande Zhou, Bin Liu, Yunxin Fan, Libing Fan

Published in: Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017

Publisher: Springer Singapore

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Abstract

Regarding the single-phase rectifier control as a Markov Decision Process (MDP) with continuous state space and discrete action space and in the meantime, we introduced a new two-objective optimization reinforcement learning framework and proposed a genetic algorithm to train the learning agent in order to optimize power factor and output DC voltage. This article analyzed the convergence of our new algorithm and presented favorable performance of numerical simulation.

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Literature
1.
Stihi O, Ooi BT (1988) A single-phase controlled-current PWM rectifier. Power Electron IEEE Trans 3(4):453–459
2.
Giri F, Abouloifa A, Lachkar I, Chaoui FZ (2010) Formal framework for nonlinear control of PWM AC/DC boost rectifiers—controller design and average performance analysis. IEEE Trans Control Syst Technol 18(2):323–335CrossRef
3.
Kim GT, Lipo TA (1995) VSI-PWM rectifier/inverter system with a reduced switch count. IEEE Trans Ind Appl 32(6):1331–1337
4.
Song HS, Keil R, Mutschler P, Van der Weem J (2003) Advanced control scheme for a single-phase PWM rectifier in traction applications. In: Conference record of the industry applications conference, 2003. Ias Meeting, vol 3 pp 1558–1565
5.
6.
Sutton RS (1998) Reinforcement learning. 11(5):126–134
7.
Kaelbling LP, Littman ML, Moore AW (1996) Reinforcement learning: a survey. J Artif Intell Res 4(1):237–285
8.
Doya K (2000) Reinforcement learning in continuous time and space. Neural Comput 12(1):219–245CrossRef
9.
Gaskett C, Wettergreen D, Zelinsky A (1999) Q-learning in continuous state and action spaces. Lect Notes Comput Sci 1747:417–428CrossRef
10.
Zitzler E, Laumanns M, Thiele L (2001) Spea2: improving the strength Pareto evolutionary algorithm
11.
Sutton RS, Mcallester D, Singh S, Mansour Y (1999) Policy gradient methods for reinforcement learning with function approximation. Adv Neural Inf Syst 12:1057–1063
12.
Fonseca CM (1993) Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of international conference on genetic algorithms, pp 416–423
13.
Horn J, Nafpliotis N, Goldberg DE (1994) A niched Pareto genetic algorithm for multiobjective optimization. In: IEEE world congress on computational intelligence, proceedings of the first ieee conference on evolutionary computation, 1994, vol 1, pp 82–87
14.
Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Springer, Berlin HeidelbergCrossRef
15.
Cichosz P (1995) Truncating temporal differences: on the efficient implementation of td(lambda) for reinforcement learning 2:287–318
16.
Bouzy B, Chaslot G (2006) Monte-carlo go reinforcement learning experiments. 187–194
17.
Baird III LC (1995) Residual algorithms: reinforcement learning with function approximation. In: Machine learning, proceedings of the twelfth international conference on machine learning, Tahoe City, California, USA, July, pp 30–37
Metadata
Title
Two-Objective Optimization Reinforcement Learning Used in Single-Phase Rectifier Control
Authors
Ande Zhou
Bin Liu
Yunxin Fan
Libing Fan
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017

Print ISBN: 978-981-10-7985-6

Electronic ISBN: 978-981-10-7986-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7986-3_103

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