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Dynamic machine lea...
Dynamic machine learning-based optimization algorithm to improve boiler efficiency
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- Blackburn, Landen D. (författare)
- University of Utah
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Tuttle, Jacob F. (författare)
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- Andersson, Klas, 1977 (författare)
- University of Utah,Chalmers tekniska högskola,Chalmers University of Technology
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- Hedengren, John D. (författare)
- Brigham Young University
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- Powell, Kody M. (författare)
- University of Utah
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(creator_code:org_t)
- Elsevier BV, 2022
- 2022
- Engelska.
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Ingår i: Journal of Process Control. - : Elsevier BV. - 0959-1524. ; 120, s. 129-149
- Relaterad länk:
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. The best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Metaheuristic optimization
- Machine learning
- Recurrent neural network
- Dynamic optimization
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