Frequency domain system identification using arbitrary signals

It is the common conviction that frequency domain system identification suffers from the drawback that it can not handle arbitrary signals without introducing systematic errors. This paper shows that it is possible to deal with non-periodic signals without any approximation, and under the same assumptions as in the time domain, by estimating simultaneously some initial conditions and the system model parameters.

[1]  E. Brigham,et al.  The fast Fourier transform , 2016, IEEE Spectrum.

[2]  Hugo Van hamme,et al.  Identification of linear dynamic systems using piecewise constant excitations: Use, misuse and alternatives , 1994, Autom..

[3]  Rik Pintelon,et al.  Frequency domain identification of linear time invariant systems under non-standard conditions , 1996, Quality Measurement: The Indispensable Bridge between Theory and Reality (No Measurements? No Science! Joint Conference - 1996: IEEE Instrumentation and Measurement Technology Conference and IMEKO Tec.

[4]  Lennart Ljung.  Some results on identifying linear systems using frequency domain data , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[5]  J. Schoukens,et al.  Parametric identification of transfer functions in the frequency domain-a survey , 1994, IEEE Trans. Autom. Control..

[6]  F. Fairman,et al.  Identification in the presence of initial conditions , 1972 .

[7]  Keith R. Godfrey,et al.  Perturbation signals for system identification , 1993 .

[8]  R. Pintelon,et al.  Identification of linear systems captured in a feedback loop , 1992, [1992] Conference Record IEEE Instrumentation and Measurement Technology Conference.

[9]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[10]  Rik Pintelon,et al.  Identification of Linear Systems: A Practical Guideline to Accurate Modeling , 1991 .