| 黄海宏,颜碧琛,王海欣.改进灰色 GM(1,1)模型的 EAST 快控电源
输出电流预测[J].电子测量与仪器学报,2021,35(5):128-136 |
| 改进灰色 GM(1,1)模型的 EAST 快控电源
输出电流预测 |
| Prediction of output current of EAST fast control power supplybased on improved grey GM (1,1) model |
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| DOI： |
| 中文关键词: EAST 快控电源 级联 H 桥 灰色 GM(1,1)预测模型 |
| 英文关键词:EAST fast control power supply non-model PID control grey GM(1 1) prediction model |
| 基金项目:国家自然科学基金（11275056）项目资助 |
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| 摘要点击次数: 825 |
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| 中文摘要: |
| 针对非模型 PID 控制难以克服参数变化、时滞的固有缺陷,为优化托卡马克装置中应对等离子体垂直不稳定位移的主
动反馈控制,通过改进灰色 GM(1,1)预测模型对基于级联 H 桥拓扑的 EAST 快控电源的输出电流进行准确预测以优化控制参
数。 灰色 GM(1,1)预测模型适用于小样本、贫信息系统,所需建模样本少、计算简易。 预测拟合序列的差异导致在对输出电流
的上凸序列进行灰色 GM(1,1)建模时存在较大预测误差,选用一种将上凸序列轴对称变换为上凹序列并建立非等间距灰色
GM(1,1)预测模型的数据变换方法,同时利用样本点给出了非等间距序列的预测时刻的估计式。 基于该改进灰色 GM(1,1)预
测模型,推导了预测模型的建模过程,通过仿真比较两种灰色 GM(1,1)预测模型对电源输出电流的预测误差,改进后突变段预
测误差率降低至 10%以下,并在实例分析中验证改进灰色 GM(1,1)预测模型的有效性。 |
| 英文摘要: |
| Since it is difficult to overcome the inherent defects of parameter changes and time lag in non-model PID control, in order to
optimize the active feedback control of the plasma vertical unstable displacement in the tokamak device. The improved grey GM (1,1)
prediction model is used to accurately predict the output current of the EAST fast control power supply based on the cascaded H-bridge
topology to optimize the control parameters. The grey GM ( 1,1) prediction model is suitable for small samples and poor information
systems, and requires fewer modeling samples and simple calculations. The difference of the predicted fitting sequence leads to the
prediction error when the grey GM (1,1) modeling is performed on the upward convex sequence of the output current. Choose a data
transformation method that transforms the upward convex sequence axisymmetrically into the upward concave sequence and establishes a
non-equidistant grey GM (1,1) prediction model. At the same time, the estimation formula of the forecast time of the non-equal interval
sequence is given by using sample points. Based on the improved prediction model, the modeling process of the prediction model is
deduced, and the prediction deviation of the two grey GM (1,1) prediction models on the output current of the power supply is compared
through simulation, and the improved grey GM (1,1) is verified in an experimental environment. After the improvement, the prediction
error rate of the mutation segment is reduced to below 10%. And verify the effectiveness of the improved grey GM ( 1,1) prediction
model in an experimental environment. |
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