Abstract
In this paper, an alternative consistent subspace identification method using parity space is proposed. The future/past input data and the past output data are used to construct the instrument variable to eliminate the noise effect on consistent estimation. The extended observability matrix and the triangular block-Toeplitz matrix are then retrieved from a parity space of the noise-free matrix using a singular value decomposition based method. The system matrices are finally estimated from the above estimated matrices. The consistency of the proposed method for estimation of the extended observability matrix and the triangular block-Toeplitz matrix is established. Compared with the classical SIMs using parity space like SIMPCA and SIMPCA-Wc, the proposed method generally enhances the estimated model efficiency/accuracy thanks to the use of future input data. Two examples are presented to illustrate the effectiveness and merit of the proposed method.
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Recommended by Associate Editor Yongping Pan under the direction of Editor Jay H. Lee. This research was supported by the National Natural Science Foundation of China under Grant 61803061, 61703347, and 61703311; Science and Technology Research Program of Chongqing Municipal Education Commission grant KJQN201800603; the Chongqing Natural Science Foundation Grant cstc2018jcyjAX0167; the Common Key Technology Innovation Special of Key Industries of Chongqing science and Technology Commission under Grant cstc2017zdcy-zdyfX0067; the Artificial Intelligence Technology Innovation Significant Theme Special Project of Chongqing science and Technology Commission under Grant cstc2017rgzn-zdyfX0014 and cstc2017rgzn-zdyfX0035.
Jie Hou received his Ph.D. degree in Control Theory and Control engineering from Dalian University of Technology in 2018. His research interests include process modelling and system identification.
Fengwei Chen received his Ph.D. degree from Universite de Lorraine in 2014. His research interests include system identification and signal processing.
Penghua Li received his Ph.D. degree in Control Theory and Control engineering from Chongqing University in 2012. His research interest includes fault diagnosis.
Zhiqin Zhu received his Ph.D. degree in Control Theory and Control engineering from Chongqing University in 2017. His research interests include image processing and identification.
Fei Liu received his Ph.D. degree in Control theory and Control engineering from Chongqing University in 2015. His research interests include intelligent mobile robot control, navigation, robot testing and assessment.
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Hou, J., Chen, F., Li, P. et al. An Improved Consistent Subspace Identification Method Using Parity Space for State-space Models. Int. J. Control Autom. Syst. 17, 1167–1176 (2019). https://doi.org/10.1007/s12555-018-0499-6
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DOI: https://doi.org/10.1007/s12555-018-0499-6