The study addresses the challenge of system uncertainty, which arises from both theoretical approximations and experimental correlation fitting. This uncertainty is compounded by the dynamic movements of space reactors, such as pitch, roll, and tilt, that influence neutronics and thermal-hydraulics models. Additional uncertainty comes from environmental disturbances affecting sensors and actuators. Quantifying these uncertainties is crucial to ensuring safe and reliable operation.
"This study proposes a new model of space nuclear reactors that can be applied to complex and uncertain environments, and clarifies the uncertainty coupling mechanism of neutronics parameters, thermal hydraulic parameters, and control system parameters of space reactors under motion conditions, which can improve the response speed and load following accuracy of the space reactor," said Dr. Run Luo, the corresponding author. "We hope this advancement will inform future research and nuclear industry practices."
Traditional PID controllers struggle with uncertain systems, often failing to achieve optimal control. To address this, the team applied multi-objective intelligent optimization methods that consider system uncertainties and time-varying characteristics. These methods enhance the reactor's adaptive control capabilities. The complexity of the space reactor and the strong parameter coupling make it challenging to manually determine optimal control parameters. To overcome this, the team employed the NSGA-II intelligent method for controller optimization, achieving more stable and precise control.
The research also analyzed the uncertainty coupling mechanisms within the reactor and implemented an intelligent control system that enhances system response and load-following accuracy under uncertain conditions. Results demonstrated that the control errors of IATE, MSE, and MPD were all lower after optimization. The optimized intelligent controllers exhibited reduced overshoot, less oscillation, and shorter settling times.
These advancements promise improved adaptive and interference-resistant control systems for advanced nuclear energy systems, offering potential benefits to future intelligent reactor control research and the nuclear industry at large.
Research Report:Dynamic model uncertainty analysis and control system multi-objective optimization of space nuclear reactor
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