Orthogonal projection based subspace identification against colored noise

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• 作者：Jie Hou ; Tao Liu ; Fengwei Chen
• 关键词：Subspace identification ; colored noise ; orthogonal projection ; extended observability matrix ; consistent estimation
• 刊名：Control Theory and Technology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：15
• 期：1
• 页码：69-77
• 全文大小：
• 刊物类别：Control; Systems Theory, Control; Optimization; Computational Intelligence; Complexity; Control, Rob
• 刊物主题：Control; Systems Theory, Control; Optimization; Computational Intelligence; Complexity; Control, Robotics, Mechatronics;
• 出版者：South China University of Technology and Academy of Mathematics and Systems Science, CAS
• ISSN：2198-0942
• 卷排序：15

文摘

In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eliminate the influence of colored noise for consistent estimation of the extended observability matrix of the plant state-space model. A shift-invariant approach is then given to retrieve the system matrices from the estimated extended observability matrix. The persistent excitation condition for consistent estimation of the extended observability matrix is analyzed. Moreover, a numerical algorithm is given to compute the estimation error of the estimated extended observability matrix. Two illustrative examples are given to demonstrate the effectiveness and merit of the proposed method.