Research of BPNN Application in Liquid Level Control of Nuclear Power Plant Steam Generator
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摘要: 蒸汽发生器(SG)液位控制性能的优劣对核电厂的安全、高效和稳定运行至关重要。基于反向传播神经网络(BPNN)比例-积分-微分(PID)控制器的基本结构,结合SG的物理特征,建立了适用于SG液位调节过程的专用的BPNN PID控制器。该BPNN PID控制器具有自匹配、自适应、自整定的特点,能够在核电厂运行过程中,实时根据被控对象运行状态的变化自动计算合适的PID参数,保证控制器始终具备优良的控制性能。该BPNN PID控制器模型经过核电厂全范围模拟机试验,在核电厂满功率运行状态下具有与原控制器相近的控制性能,但在低功率运行状态下相较于原控制器其控制性能得到显著改善。
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关键词:
- 反向传播神经网络(BPNN) /
- 比例-积分-微分(PID)控制器 /
- 蒸汽发生器(SG)液位控制
Abstract: The performance of steam generator (SG) water level control is a critical factor in ensuring the safe, efficient, and stable operation of nuclear power plants. Based on the basic structure of a Backpropagation Neural Network (BPNN) Proportional-Integral-Derivative (PID) controller and incorporating the physical characteristics of the SG, a dedicated BPNN PID controller suitable for SG water level control processes was developed. This PID controller features self-matching, self-adaptive, and self-tuning capabilities, enabling it to automatically calculate appropriate PID parameters in real time based on changes in the operating conditions of the controlled object during nuclear power plant operations. This ensures consistently excellent control performance of the controller. The BPNN PID controller model was subject to full-scope simulator tests for nuclear power plants. While maintaining control performance comparable to the original controller under full-power operation conditions of nuclear power plants, it demonstrated significantly improved control performance under low-power operation conditions. -
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