Identification of Closed Loop Projection Subspace for Motor Based on Hankel Correlation Function

doi:10.16182/j.issn1004731x.joss.201806008

Abstract

Abstract: To solve estimation deviation problem of model parameter in the closed-loop system identification, the subspace identification model and state space model based on the estimation of the correlation function are presented, and through the correlation function estimation and zero space followed by projection, the block Hankel matrix of identification framework was filled so as to obtain the scope of the extended observability matrix; on the basis of the same projection on the time offset set of related data, the RQ decomposition of the projection is calculated by numerical calculation, and the dynamic estimation of the system model is obtained. The simulation experiment on the closed loop system of induction motor indicates that the proposed method has higher identification accuracy, and it is verified by the hardware in the real environment.

Key words: correlation function, Hankel matrix, closed loop system, subspace identification, induction motor

CLC Number:

TM75

She Minghong. Identification of Closed Loop Projection Subspace for Motor Based on Hankel Correlation Function[J]. Journal of System Simulation, 2018, 30(6): 2058-2065.

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