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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2023.10
- 수록면
- 1,259 - 1,264 (6page)
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초록· 키워드
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The model predictive control (MPC) strategy has been successfully applied to the control of Post-combustion CO₂ capture (PCC) systems. This paper firstly implements the control requirement of three inputs and two outputs of the system by using a multivariable MPC strategy based on the strong coupling characteristics of the PCC system between multiple variables, and then proposes a model predictive control method based on gain scheduling for the operation of the PCC system with strong nonlinearity in a wide range of operating conditions. By modeling the system transfer function at typical operating points, combining the gain scheduling strategy to model the entire system, and using predictive control techniques to ensure the global optimized quality of the control system. The simulation results show that, compared with the conventional MPC control algorithm, the predictive control method based on gain scheduling can quickly track load changes in a wide range of operating conditions, and each output of the coordinated control system is regulated to follow the set value faster, with smaller dynamic deviation, faster control actuator action, relatively smooth control action changes, and good stability.
목차
Abstract
1. INTRODUCTION
2. MODELING AND DYNAMIC ANALYSIS OF PCC SYSTEM
3. MULTIVARIATE MODEL PREDICTIVE OPTIMAL CONTROL OF PCC SYSTEM
4. GAIN SCHEDULING MODEL PREDICTIVE CONTROL OF PCC
5. CONCLUSION
REFERENCES
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