Singular value decomposition based learning identification for linear time-varying systems: From recursion to iteration
Fazhi Song
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorCorresponding Author
Li Li
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Correspondence Li Li, Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, No. 92, Xidazhi Street, Harbin, China.
Email: [email protected]
Search for more papers by this authorYang Liu
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorYue Dong
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorFazhi Song
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorCorresponding Author
Li Li
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Correspondence Li Li, Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, No. 92, Xidazhi Street, Harbin, China.
Email: [email protected]
Search for more papers by this authorYang Liu
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorYue Dong
Center of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin, China
Key Lab of Ultra-precision Intelligent Instrumentation, Harbin Institute of Technology, Ministry of Industry and Information Technology, Harbin, China
Search for more papers by this authorAbstract
System identification is a critical task in various engineering applications such as motion control, signal processing and robotics. In this article, the identification of linear time-varying (LTV) systems that perform tasks repetitively over a finite-time interval is investigated. Traditional LTV system identification typically adopts recursive algorithms in the time domain, which are incapable of tracking drastic-varying parameters and are subject to estimation lag and numerical instability. To address these issues, this article proposes the utilization of an iteration axis in addition to the time axis for estimating repetitive time-varying parameters. Specifically, the proposed approach involves an estimation algorithm for the time-varying parameters based on a recursive least squares (RLS) method along the iteration axis, as well as an update algorithm for the covariance matrix based on singular value decomposition (SVD) to enhance numerical stability. Additionally, a bias compensation method based on noise variance estimation is introduced for the sake of eliminating estimation error induced by measurement noise. Numerical comparisons with existing methods are conducted to demonstrate the effectiveness and superiority of the proposed method.
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
Data sharing is not suitable for the article because no datasets are came into being and analyzed during the currently discuss period.
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