Researchers from University of South China, Tsinghua University and Technical University of Munich have developed a whole system uncertainty model and an Intelligent optimized power control system of the space nuclear reactor with faster response, higher control accuracy and stronger adaptability under uncertainty conditions. These research results provide new ideas and solutions for improving the intelligence level and autonomous control capability of advanced nuclear energy systems in complex environments.
System Multi-parameters Coupling Uncertainty and Sensitivity Analysis
Both the theoretical simulation approximation and empirical correlation fitting in the experimental process cause system model uncertainty. Furthermore, the device of the space reactor would be accompanied by multi-degree of freedom movements such as ups, downs, swings, and tilts in the changeable space environment, which results in parameter uncertainty of the reactor neutronics and thermal-hydraulics model. At the same time, the sensors and actuators of the control system would also bring uncertainty due to environmental disturbances. System uncertainty of space reactors must be quantified to ensure 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.”
More Stable and Precise Nuclear Reactor Control
it is difficult for traditional PID controllers to adapt for the nuclear reactor control of uncertainty systems and could not obtain optimal control performance. On the one hand, considering the system uncertainty and time-varying characteristics of space reactors, multi-objective intelligent optimization methods were applied to the controller design of uncertainty systems to improve the adaptive control capabilities of the space reactor in this study. On the other hand, due to the complexity of the space reactor system and the strong coupling between subsystem parameters, the experiential acquisition process of the optimal control parameters under uncertainty conditions is very inefficient and time-consuming, and it is difficult to obtain the global optimal solution. Compared with the controller optimization design that rely on manual experience, the NSGA-II intelligent method is applied for multi-objective optimization the controller design problems. A more stable and precise space reactor control were obtained in this study.
Intelligent Optimization Design Leads to Stronger Adaptability
The research team’s analysis revealed uncertainty coupling mechanism of neutronics parameters, thermal hydraulic parameters, and control system parameters of space reactors under motion conditions. In addition, the research team designed an intelligent control system to improve system response speed and load following accuracy under uncertainty conditions. The research results show that the control errors of IATE, MSE and MPD after optimization are all lower than those of values before optimization, and the optimized intelligent controllers have lower overshoot, less oscillation and shorter time to reach a new steady state when considering system uncertainty.
This research can provide new ideas for the control problems of advanced nuclear energy systems and improve the anti-interference and adaptive control capabilities of nuclear reactors in complex and uncertain environments, which could be applied for future intelligent control research of advanced reactors and nuclear industry practices.
The complete study is accessible Via DOI: 10.1007/s41365-025-01710-7
Nuclear Science and Techniques
Computational simulation/modeling
Not applicable
Dynamic model uncertainty analysis and control system multi-objective optimization of space nuclear reactor
10-May-2025