Recursive Identification Study of State space Model of Linear Time-varying System

Ni Zhi-yu1,Wu Zhi-gang1,2

Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (4) : 8-14.

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PDF(1547 KB)
Journal of Vibration and Shock ›› 2016, Vol. 35 ›› Issue (4) : 8-14.

Recursive Identification Study of State space Model of Linear Time-varying System

  • Ni Zhi-yu1,Wu Zhi-gang1,2
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Abstract

A novel recursive form for identifying state space model of linear time-varying system is presented in this paper. In contrast with the frequently-used identification method based on the singular value decomposition (SVD) and least squares estimation, the proposed recursive method is derived from the signal subspace projection theory. The time-varying state space model of system is obtained from the new signal subspace matrix by reconstructing the relation of input and output data. Comparing with the existing identification method, the computation time of the proposed approach is decreased because the recursive method does not require the SVD of matrix. Particularly when the system order is high, the advantage of computational efficiency of the recursive method is significant. In numerical simulation examples, the identified results and computational efficiency are compared with the classical time-varying eigensystem realization algorithm (TV-ERA) based on SVD. The simulation results show that the proposed approach can be applied to identify state space model of linear time-varying system and it has higher computational efficiency than TV-ERA.

Key words

linear time-varying system / recursive subspace method / state space model / parameter identification

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Ni Zhi-yu1,Wu Zhi-gang1,2. Recursive Identification Study of State space Model of Linear Time-varying System[J]. Journal of Vibration and Shock, 2016, 35(4): 8-14

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