Abstract In multi-reactor and multi-turbine nuclear power plants (MMNPP), several reactor units working in parallel provide steam to turbines that generate power for different purposes. Due to a common steam header that all turbines are connected to, changes in the power output of one turbine can influence the performance of other turbines (and their power output) when operating in load following scenarios. This may threaten the stable and safe operation of the plant. To avoid the coupling effect between the power outputs of turbines, this paper presents a composite control method to decouple turbine power from each other. This (power) decoupling control strategy is composed of a neural network based inverse system (NNIS) and a robust controller. The neural network inverse system approaches the inverse system of the original nonlinear system. The robust controller, containing PI controllers and integrators, is added to the NNIS to construct a closed loop decoupling controller with strong robustness. Simulation results indicate that the proposed decoupling controller has excellent power decoupling capabilities and robust performance as well as fast tracking capability.

中文翻译：

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一种基于神经网络的逆系统控制策略解耦多堆多汽核电厂汽轮机功率

摘要 在多反应堆和多涡轮核电站 (MMNPP) 中，多个并行工作的反应堆单元向涡轮机提供蒸汽，涡轮机为不同目的发电。由于所有涡轮机都连接到一个公共蒸汽集管，当在负载跟随场景中运行时，一台涡轮机的功率输出变化会影响其他涡轮机的性能（及其功率输出）。这可能会威胁到工厂的稳定和安全运行。为了避免涡轮机功率输出之间的耦合效应，本文提出了一种复合控制方法来使涡轮机功率相互解耦。这种（功率）解耦控制策略由基于神经网络的逆向系统 (NNIS) 和鲁棒控制器组成。神经网络逆系统逼近原非线性系统的逆系统。在NNIS中加入包含PI控制器和积分器的鲁棒控制器，构建鲁棒性强的闭环解耦控制器。仿真结果表明，所提出的解耦控制器具有出色的功率解耦能力和稳健的性能以及快速跟踪能力。