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Stochastic Distribution Control of Singular Systems: Output PDF Shaping 被引量：1

Stochastic Distribution Control of Singular Systems: Output PDF Shaping
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摘要 This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that the output PDF is made as close as possible to a given PDF.Based on the B-spline neural network approximation of the output PDF, the control algorithm is formulated by extending the developed PDF control strategies of non-singular systems to singular systems. It has been shown that under certain conditions the stability of the closed-loop system can be guaranteed. Simulation examples are given to show the effectiveness of the proposed control algorithm. This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that the output PDF is made as close as possible to a given PDF. Based on the B-spline neural network approximation of the output PDF, the control algorithm is formulated by extending the developed PDF control strategies of non-singular systems to singular systems. It has been shown that under certain conditions the stability of the closed-loop system can be guaranteed. Simulation examples are given to show the effectiveness of the proposed control algorithm.
作者 H.YUE A.J.A.LEPRAND H.WANG
机构地区 InstituteofAutomation ControlSystemsCentre instituteofAutomation
出处 《自动化学报》 EI CSCD 北大核心 2005年第1期151-160,共10页 Acta Automatica Sinica
基金 Supported by the Research Fund of Chinese Academy of Sciences (2004-1-4)
关键词 随机分布控制 单系统 PDF显示输出 动态随机系统 概率密度函数 Singular systems, dynamic stochastic systems, probability density function (PDF), B-splines neural networks
分类号 TP273 [自动化与计算机技术—检测技术与自动化装置]
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参考文献29

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同被引文献12

  • 1Guo L, Zhao K Y, Feng C B. Proper Output Feedback H∞ Control for Descriptor Systems: A Convex Optimization Approach [C] // Advances in Natural Computation. Berlin, Heidelberg: Springer, 2005: 698- 702.
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自动化学报
2005年 第1期

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