Abstract The pressurizer system (PRZ) plays a vital role in the operation of pressurized water reactors (PWRs). The PRZ is inherently a non-linear, time-variant system, and hence the PRZ modeling with transfer function or linear time-invariant state-space forms is not accurate enough. In this paper, the thermal-hydraulic behavior of the PRZ is modeled by RELAP5 thermal-hydraulic code that is one of the best modeling codes offered for the PRZ system. Although the RELAP5 best-estimate code is appropriate for PRZ modeling, the RELAP5 is not capable to implement the advanced controllers. As first-time, to eliminate this issue, the RELAP5 code and MATLAB software are coupled to use the capabilities of MATLAB (the ability to implement advanced controllers) and RELAP5 (the best model for the PRZ system) simultaneously. Accordingly, this coupling provides a new platform for designing and implementing various intelligent and advanced controllers for PRZ pressure and level in RELAP5 code. Likewise, after providing the platform for implementing intelligent controllers, a novel supervisory control based on neural network PID (NN-PID) controllers is designed for the PRZ pressure and level control. Also, the PRZ system is modeled as a MIMO system with consideration of the PRZ pressure and level interactions. Furthermore, as a case study, the advanced designed control system is applied to adjust the pressure and level of PRZ in a VVER-1000 type nuclear power plant. The study results show that this newly designed control system is able to control the PRZ pressure and level efficiently and effectively in several conditions. Therefore, the proposed methodology as a novel design of PRZ control can be applied and developed in new generations of nuclear power plants and pressurized test loops.

中文翻译：

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基于神经网络PID控制器的增压系统监控设计与应用

摘要 加压系统（PRZ）在压水反应堆（PWR）的运行中起着至关重要的作用。PRZ 本质上是一个非线性、时变系统，因此具有传递函数或线性时不变状态空间形式的 PRZ 建模不够准确。在本文中，PRZ 的热工水力行为由 RELAP5 热工水力代码建模，该代码是为 PRZ 系统提供的最佳建模代码之一。尽管 RELAP5 最佳估计代码适用于 PRZ 建模，但 RELAP5 无法实现高级控制器。作为第一次，为了消除这个问题，RELAP5 代码和 MATLAB 软件结合起来，同时使用 MATLAB（实现高级控制器的能力）和 RELAP5（PRZ 系统的最佳模型）的功能。因此，这种耦合为在 RELAP5 代码中设计和实现 PRZ 压力和水平的各种智能和高级控制器提供了一个新平台。同样，在提供了实现智能控制器的平台后，设计了一种基于神经网络PID（NN-PID）控制器的新型监控控制，用于PRZ压力和液位控制。此外，考虑到 PRZ 压力和电平相互作用，PRZ 系统被建模为 MIMO 系统。此外，作为案例研究，先进设计的控制系统被应用于调节 VVER-1000 型核电站中 PRZ 的压力和水平。研究结果表明，这种新设计的控制系统能够在多种条件下有效地控制 PRZ 压力和液位。所以，