location: Current position: Prof. Tao Liu >> Scientific Research >> Paper Publications

Subspace model identification under load disturbance with unknown transient and periodic dynamics

Hits:

Indexed by:Journal Papers

Date of Publication:2020-01-01

Journal:JOURNAL OF PROCESS CONTROL

Included Journals:EI、SCIE

Volume:85

Page Number:100-111

ISSN No.:0959-1524

Key Words:Subspace identification; load disturbance; deterministic system response; oblique projection; consistent estimation

Abstract:To overcome the influence from load disturbance with unknown transient and periodic dynamics, as often encountered when performing identification tests in engineering applications, a bias-eliminated subspace model identification method is proposed to realize consistent estimation, which can be used for both open- and closed-loop systems. By decomposing the output response into disturbed and undisturbed components, an oblique projection is subtly introduced to eliminate the disturbance and noise impact so as to obtain unbiased estimation on the deterministic system state matrices, while the disturbance response dynamics could be estimated. In particular, a specific algorithm based on minimizing the output prediction error is given to find out the disturbance period if exists, such that the disturbance effect can be eliminated by the above projection regardless of the disturbance waveform and magnitude. A shift-invariant approach is then given to retrieve the deterministic state matrices. Consistent estimation on the deterministic system matrices is analyzed with a proof. A benmark example from the literature and an industrial injection molding process are used to demonstrate the effectiveness and merit of the proposed method. (C) 2019 Published by Elsevier Ltd.

Pre One:Extended state observer based indirect-type ILC for single-input single-output batch processes with time- and batch-varying uncertainties

Next One:管道传输气体超声波流量计的新设计方法