Blind Nonparametric Estimation of SISO Continuous-time Systems

Elton, AugustusSchool of Engineering, University of Newcastle, Callaghan, Australia (author)

QC 20240222 Part of ISBN 9781713872344
Blind system identification is aimed at finding parameters of a system model when the input is inaccessible. In this paper, we propose a blind system identification method that delivers a single-input single-output, continuous-time model in a nonparametric kernel form. We take advantage of the representer theorem to form a joint maximum a posteriori estimator of the input and system impulse response. The identified system model and input are optimised in sequence to overcome the blind problem with generalised cross validation used to select appropriate hyperparameters given some fixed input sequence. We demonstrate via Monte Carlo simulations the accuracy of the method in terms of estimating the input.

González, Rodrigo A.Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands (author)
Welsh, James S.School of Engineering, University of Newcastle, Callaghan, Australia (author)
Oomen, TomDepartment of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Delft Center for Systems and Control, Delft University of Technology, The Netherlands (author)
Rojas, Cristian R.,1980-KTH,Reglerteknik(Swepub:kth)u10v97p2 (author)
School of Engineering, University of Newcastle, Callaghan, AustraliaDepartment of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands (creator_code:org_t)

By the author/editor: Elton, Augustus; González, Rodrig ...; Welsh, James S.; Oomen, Tom; Rojas, Cristian ...

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ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Control Engineer ...

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