Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions - A frequency domain approach

IEEE Transactions on Automatic Control

Volumn 43, Issue 2, 1998, Pages 176-190

  Schoukens, Johan ^a,c   Dobrowiecki, Tadeusz ^b,c   Pintelon, Rik ^a,c  

^a VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

^b BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

^c IEEE   (Belgium)

Author keywords

Model selection and validation; Nonlinear systems; System identification

Indexed keywords

APPROXIMATION THEORY; CONVERGENCE OF NUMERICAL METHODS; FREQUENCY DOMAIN ANALYSIS; LINEAR CONTROL SYSTEMS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; PROBABILITY; RANDOM PROCESSES; SIGNAL DISTORTION; TRANSFER FUNCTIONS;

MODEL SELECTION; MODEL VALIDATION; RANDOM MULTISINE EXCITATIONS; RELATED LINEAR DYNAMIC SYSTEMS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 0031999205     PISSN: 00189286     EISSN: None     Source Type: Journal    
DOI: 10.1109/9.661066     Document Type: Article

References (25)

1. J. S. Bendat, Nonlinear System Analysis and Identification from Random Data. New York: Wiley, 1990.
2. J. S. Bendat and A. G. Piersol, Engineering Applications of Correlation and Spectral Analysis. New York: Wiley, 1980.
3. S. A. Billings, "Identification of nonlinear systems: A survey," Proc. Inst. Elec. Eng., 1980, vol. 127, pt. D, pp. 272-285.
4. S. A. Billings and S. Y. Fakhour, "Identification of systems containing linear dynamic and static nonlinear elements," Automatica, vol. 18, no. 1, pp. 15-26, 1982.
5. S. A. Billings and Q. H. Tao, "Model validity tests for nonlinear signal processing applications," Int. J. Contr., vol. 54, no. 1, pp. 157-194, 1991.
6. D. R. Brillinger, Time Series, Data Analysis and Theory. New York: McGraw-Hill, 1981.
7. L. O. Chua and C.-Y. Ng, "Frequency domain analysis of nonlinear systems: General theory," Electron. Circuits Syst., vol. 3, no. 4, pp. 165-185, 1979.
8. C. Evans, "Identification of linear and nonlinear systems using multisine test signals," Ph.D. dissertation, Dept. Electronics and IT, Univ. Glamorgan, 1998.
9. G. C. Goodwin, M. Gevers, and B. Ninness, "Quantifying the error in estimated transfer functions with applications to model order selection," IEEE Trans. Automat. Contr., vol. 37, pp. 913-928, 1992.
10. L. Guo and L. Ljung, "The role of model validation for assessing the size of the unmodeled dynamics," in Proc. 33nd IEEE Conf. Decis. Contr., Lake Buena Vista, FL, Dec. 14-16, 1994, pp. 3894-3899.
11. L. Ljung, System Identification. Theory for the User. Englewood Cliffs, NJ: Prentice-Hall, 1987.
12. E. Lukacs, Stochastic Convergence. New York, Academic, 1975.
13. J. M. Mendel, "Tutorial on higher-order statistics (spectra) in signal processing and system theory: Theoretical results and some applications," in Proc. IEEE, vol. 79. pp. 278-305, 1991.
14. C. L. Nikias and J. M. Mendel, "Signal processing with higher-order spectra," IEEE Signal Processing Mag., July 1993, pp. 10-36.
15. C. L. Nikias and A. P. Petropulu, Higher-Order Spectra Analysis, Signal Processing Series. Englewood Cliffs, NJ: Prentice-Hall, 1993.
16. A. E. Nordsjö, B. M. Ninness, and T. Wigren, "Quantifying model errors caused by nonlinear undermodeling in linear system identification," in Preprints 13th World Congr. IFAC, San Francisco, CA, 1996, vol. I, pp. 145-149.
17. B. Picinbono, Random Signals and Systems, Signal Processing Series. Englewood Cliffs, NJ: Prentice-Hall, 1993.
18. M. Schetzen, The Volterra and Wener Theories of Nonlinear Systems. New York: Wiley, 1980.
19. J. Schoukens and R. Pintelon, Identification of Linear Systems: A Practical Guideline to Accurate Modeling. London, U.K.: Pergamon, 1991.
20. J. Schoukens, P. Guillaume, and R. Pintelon, "Design of broadband excitation signals," in Perturbation Signals for System Identification, K. Godfrey, Ed. Englewood Cliffs, NJ: Prentice-Hall, 1993, pp. 126-159.
21. J. Schoukens and R. Pintelon, "Quantifying model errors of identified transfer functions," IEEE Trans. Automat. Contr., vol. 39, pp. 1733-1737, Aug. 1994.
22. J. Schoukens, T. Dobrowiecki, and R. Pintelon, "Identification of linear systems in the presence of nonlinear distortions - Parts I and II," in Proc. 34th Conf. Decision Contr., New Orleans, LA, Dec. 13-15, 1995, pp. 1216-1227.
23. J. Schoukens and R. Pintelon, "Identification and validation of errors-invariables models using a sample covariance matrix obtained from small data sets," Second Int. Wkshp. Errors-in-Variables Modeling, Belgium, 1996, pp. 59-68.
24. J. Schoukens, R. Pintelon, G. Vandersteen, and P. Guillaume, "Frequency domain system identification using nonparametric noise models estimated from a small number of data sets," Automatica, vol. 33, no. 5, pp. 991-994, 1997.
25. T. Söderström, "Convergence properties of the generalized least squares identification method," Automatica, vol. 10, pp. 617-626, 1974.