Application of system identification methodology for a model predictive control of oil refinery process정유 공정 모델 예측 제어를 위한 시스템 식별 방법론 적용
Competition in the crude oil refining industry, an industry that emits carbon, is intensifying due to the global trend of carbon reduction. Automating refining process control is critical to maintaining a competitive edge. Among the control automation technologies, the predictive model control method is the most effective, but it has a disadvantage in that it is difficult to identify the control target system. In this paper, the performance improvement method of the machine learning technique for system identification is presented and the performance improvement is verified by applying it to a commercial refinery.
- Advisors
- Park, Jin Kyuresearcher; 박진규researcher
- Description
- 한국과학기술원 :산업및시스템공학과,
- Publisher
- 한국과학기술원
- Issue Date
- 2023
- Identifier
- 325007
- Language
- eng
- Description
학위논문(석사) - 한국과학기술원 : 산업및시스템공학과, 2023.2,[iii, 17 p. :]
- Keywords
System identification▼aModel predictive control▼aMachine learning; 시스템식별▼a모델예측제어▼a머신러닝
- Appears in Collection
- IE-Theses_Master(석사논문)
- Files in This Item
- There are no files associated with this item.
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