NSGA-II algorithm-based LQG controller design for nuclear reactor power control
•A state space model of the reactor core was derived.•The Linear Quadratic Gaussian (LQG) controller was designed.•The linear quadratic regulator (LQR) weighting factor was optimized by elitist nondominated sorting genetic algorithm version II (NSGA-II) algorithm.•The LQG controller optimized based...
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Veröffentlicht in: | Annals of nuclear energy 2022-05, Vol.169, p.108931, Article 108931 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A state space model of the reactor core was derived.•The Linear Quadratic Gaussian (LQG) controller was designed.•The linear quadratic regulator (LQR) weighting factor was optimized by elitist nondominated sorting genetic algorithm version II (NSGA-II) algorithm.•The LQG controller optimized based on NSGA-II method not only has fast response, high control accuracy and good stability, but also has good robustness and can obtain superior reactor power control performance.
The design of reactor power control system is closely related to the safety and economy of nuclear power plants. To improve its power control performance, this study takes a pressurized water reactor as the research object. The nonlinear dynamic mathematical model and its state space model were first derived; Then the Linear Quadratic Gaussian (LQG) optimal control method was adopted to design the reactor power controller; Furthermore, the multi-objective optimization of the linear quadratic regulator (LQR) weighting coefficient is carried out based on the elitist nondominated sorting genetic algorithm version II (NSGA-II). The results show that the LQG controller optimized based on NSGA-II method not only has fast response, high control accuracy and good stability, but also has good robustness and can obtain superior reactor power control performance. |
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ISSN: | 0306-4549 1873-2100 |
DOI: | 10.1016/j.anucene.2021.108931 |