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Identification of Time-Delay Systems using the Subspace Method


Affiliations
1 Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
 

Background/Objectives: A new algorithm for identification of LTI delayed systems by using the subspace method is proposed. The idea is based on removing the unknown triangular Toeplitz matrix by using the orthogonal of input Hankel matrix to obtain the observability matrix. Methods: The method is used for both deterministic and stochastic representations. Finding: The main feature of the present work over similar possible algorithms is that with a relatively low number of iterations we get the exact results. Application/Improvements: Two examples are shown to illustrate the validity of the method.

Keywords

Input Hankel Matrix, LTI Delayed Systems, Observability Matrix, Triangular Toeplitz Matrix
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  • Identification of Time-Delay Systems using the Subspace Method

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Authors

Seyed Hessam Nasehi
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Seyed Hadi Nasehi
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Mahmood Samavat
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Mohammad Ali Vali
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

Abstract


Background/Objectives: A new algorithm for identification of LTI delayed systems by using the subspace method is proposed. The idea is based on removing the unknown triangular Toeplitz matrix by using the orthogonal of input Hankel matrix to obtain the observability matrix. Methods: The method is used for both deterministic and stochastic representations. Finding: The main feature of the present work over similar possible algorithms is that with a relatively low number of iterations we get the exact results. Application/Improvements: Two examples are shown to illustrate the validity of the method.

Keywords


Input Hankel Matrix, LTI Delayed Systems, Observability Matrix, Triangular Toeplitz Matrix



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i7%2F130877