输出概率密度函数形状的多步预测控制

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输出概率密度函数形状的多步预测控制

王宏, 张金芳, 岳红

文章导航 > 自动化学报 > 2005 > 31(2): 274-279

王宏, 张金芳, 岳红. 输出概率密度函数形状的多步预测控制. 自动化学报, 2005, 31(2): 274-279.

引用本文:

王宏, 张金芳, 岳红. 输出概率密度函数形状的多步预测控制. 自动化学报, 2005, 31(2): 274-279.

WANG Hong, ZHANG Jin-Fang, YUE Hong. Multi-step Predictive Control of a PDF-shaping Problem. ACTA AUTOMATICA SINICA, 2005, 31(2): 274-279.

Citation:

WANG Hong, ZHANG Jin-Fang, YUE Hong. Multi-step Predictive Control of a PDF-shaping Problem. ACTA AUTOMATICA SINICA, 2005, 31(2): 274-279.

王宏, 张金芳, 岳红. 输出概率密度函数形状的多步预测控制. 自动化学报, 2005, 31(2): 274-279.

引用本文:

王宏, 张金芳, 岳红. 输出概率密度函数形状的多步预测控制. 自动化学报, 2005, 31(2): 274-279.

WANG Hong, ZHANG Jin-Fang, YUE Hong. Multi-step Predictive Control of a PDF-shaping Problem. ACTA AUTOMATICA SINICA, 2005, 31(2): 274-279.

Citation:

WANG Hong, ZHANG Jin-Fang, YUE Hong. Multi-step Predictive Control of a PDF-shaping Problem. ACTA AUTOMATICA SINICA, 2005, 31(2): 274-279.

输出概率密度函数形状的多步预测控制

1.
Institute of Automation, Chinese Academy of Sciences, Beijing, 100080, P.R.China

通讯作者:
张金芳

计量
- 文章访问数: 2433
- HTML全文浏览量: 82
- PDF下载量: 1385
- 被引次数: 0
出版历程
- 收稿日期: 2003-03-14
- 修回日期: 2004-09-19
- 刊出日期: 2005-03-20

Multi-step Predictive Control of a PDF-shaping Problem

1.
Institute of Automation, Chinese Academy of Sciences, Beijing, 100080, P.R.China

More Information

Corresponding author: ZHANG Jin-Fang

摘要: A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore converts the PDF-shaping into the control of B-spline weights vector. The Diophantine equation is then introduced to formulate the predictive PDF model, based on which a moving-horizon control algorithm is developed so as to realize the predictive PDF tracking performance.
- Probability density function (PDF) /
- predictive control /
- B-spline functions /
- stochastic distribution control
Abstract: A predictive control strategy is proposed for the shaping of the output probability density function (PDF) of linear stochastic systems. The B-spline neural network is used to set up the output PDF model and therefore converts the PDF-shaping into the control of B-spline weights vector. The Diophantine equation is then introduced to formulate the predictive PDF model, based on which a moving-horizon control algorithm is developed so as to realize the predictive PDF tracking performance.
- Probability density function (PDF) /
- predictive control /
- B-spline functions /
- stochastic distribution control

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文章访问数: 2433
HTML全文浏览量: 82
PDF下载量: 1385
被引次数: 0

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