基于对角回归神经网络的饱和式蒸汽发生器水位控制

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DRNN Based Control for Water Level of Saturated Steam Generator

1. School of Electric Engineering, Southwest Jiaotong University, Chengdu, 610031, China;
2. Nuclear Power Institute of China, Chengdu, 610041, China;
3. Atlantic Nuclear Services Ltd, Canada

摘要: 神经网络具有较强的自学习和自适应能力,本文设计了基于对角回归神经网络(DRNN)的控制系统,选择合适的学习率,实现饱和式蒸汽发生器水位变化率的快速稳定辨识和自适应控制。仿真结果表明,蒸汽发生器水位的控制效果良好。
- 对角回归神经网络 /
- 蒸汽发生器 /
- 水位控制
Abstract: The neural network has strong self-learning and self-adapting abilities.Presented in this paper is a diagonal recurrent neural network-based control system that is applied to quick and stable identification and self-adaptive level control of the saturated steam generator.The simulation results demonstrate that the developed control system is with good control performances.
- Diagonal recurrent neural network /
- Steam generator /
- Level control