A Plant Control Technology Using Reinforcement Learning Method with Automatic Reward Adjustment
Author:
Affiliation:
1. Energy & Environmental Systems Research Laboratory, Hitachi Ltd.
2. Information Control System Division, Hitachi Ltd.
Publisher
Institute of Electrical Engineers of Japan (IEE Japan)
Subject
Electrical and Electronic Engineering
Link
https://www.jstage.jst.go.jp/article/ieejeiss/129/7/129_7_1253/_pdf
Reference18 articles.
1. (1) U. S. Environmental Protection Agency: http://www.epa.gov/air/oaq_caa.html/
2. (3) Power Plant Optimization Industry Experience: 2005 Update. EPRI, Palo Alto (2005)
3. (4) T. R. Rangaswamy, J. Shanmugam, and K. P. Mohammed:“Adaptive Fuzzy Tuned PID Controller for Combustion of Utility Boiler”, Control and Intelligent Systems, Vol. 33, No. 1, pp. 63-71 (2005)
4. (5) R. C. Booth and W. B. Roland:“Neural Network-Based Combustion Optimization Reduces NOx Emissions While Improving Performance”, Proc. of Dynamic Modeling Control Applications for Industry Workshop, pp. 1-6 (1998)
5. (6) B. J. Radl:“Neural networks improve performance of coal-fired boilers”, CADDET Energy Efficiency Newsletter, No. 1, pp. 4-6 (1999)
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