Bias-eliminated subspace identification by LQ decomposition against unexpected disturbance with deterministic dynamics

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• 英文论文题名：Bias-eliminated subspace identification by LQ decomposition against unexpected disturbance with deterministic dynamics
• 论文作者：Shengnan Zhang ; Jie Hou ; Tao Liu
• 英文论文作者：Shengnan Zhang ; Jie Hou ; Tao Liu ; Institute of Advanced Control Technology ; Dalian University of Technology
• 年：2017
• 作者机构：Institute of Advanced Control Technology,Dalian University of Technology;
• 英文论文关键词：Subspace identification ; load disturbance ; LQ decomposition ; consistent estimation
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：TP273
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：5
• 文件大小：174k
• 原文格式：D
• 会议级别：全国

摘要

In this paper, a bias-eliminated subspace identification method is proposed for application under unexpected disturbance with deterministic dynamics. The linear superposition principle is adopted to decompose the output response into deterministic, disturbed and stochastic components, such that an LQ decomposition is developed to eliminate the disturbance and noise effect for consistent estimation of the deterministic system state. Consequently, the least-squares fitting algorithm is based on the estimated system state is used to retrieve the state matrices. An illustrative example is shown to demonstrate the effectiveness of the proposed method.
In this paper, a bias-eliminated subspace identification method is proposed for application under unexpected disturbance with deterministic dynamics. The linear superposition principle is adopted to decompose the output response into deterministic, disturbed and stochastic components, such that an LQ decomposition is developed to eliminate the disturbance and noise effect for consistent estimation of the deterministic system state. Consequently, the least-squares fitting algorithm is based on the estimated system state is used to retrieve the state matrices. An illustrative example is shown to demonstrate the effectiveness of the proposed method.

引文

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