On intelligent extraction of an internal signal in a wiener system consisting of a linear block followed by hard-nonlinearity

Informatica (Netherlands)

Volumn 24, Issue 1, 2013, Pages 35-58

  Kazlauskas, Kazys ^a   Pupeikis, Rimantas ^a  

^a VILNIUS UNIVERSITY   (Lithuania)

Author keywords

hard nonlinearity; internal signal; observations; parametric identification; Wiener systems

Indexed keywords

HARD NONLINEARITIES; INTERNAL SIGNALS; OBSERVATIONS; PARAMETRIC IDENTIFICATION; WIENER SYSTEMS;

EXTRACTION;

EID: 84876227628     PISSN: 08684952     EISSN: None     Source Type: Journal    
DOI: 10.15388/informatica.2013.383     Document Type: Article

References (24)

1. Armstrong-Hélouvry, B., Dupont, P., Canudas de Wit, C. (1994). A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica, 30(7), 1083-1138. (Pubitemid 124008280)
2. Åström, K.J., Wittenmark, B. (1996). Computer-Controlled Systems: Theory and Design, 3rd edn. Prentice Hall, New York.
3. Bai, E.W. (2002). Identification of linear systems with hard input nonlinearities of known structure. Automatica, 38, 853-860.
4. Canudas de Wit, C., Olsson, H., Åström, K.J., Lischinsky, P. (1995). A new model for control of systems with friction. Transactions on Automatic Control, 40(3), 419-425.
5. Desoer, C.A., Shahruz, S.M. (1986). Stability of dithered nonlinear systems with backlash or hysteresis. International Journal of Control, 43(4), 1045-1060. (Pubitemid 16494096)
6. Hagenblad, A. (1998). Identification ofWienermodels. Technical report LiTH-ISY-R-2031, Department of Electrical Engineering, Linköping University, SE-581 83 Linköping, Sweden.
7. Ljung, L. (1999). System Identification. Theory for the User, 2nd edn. Prentice-Hall, New York.
8. Malinvaud, E. (1969). Statistical Methods of Econometrics. North-Holland, Amsterdam.
9. Pupeikis, R. (2003). Identification of piecewise affine Wiener systems using data partition. Technical report LiTH-ISY-R-2523, Department of Electrical Engineering, Linköping University, SE-581 83 Linköping, Sweden.
10. Pupeikis, R. (2005). On the identification of Wiener systems having saturation-like functions with positive slopes. Informatica, 16(1), 131-144. (Pubitemid 40900341)
11. Pupeikis, R. (2005). On the identification of Hammerstein-Wiener systems. Lietuvos matematikos rinkinys, 45(spec. nr.), 509-514.
12. Pupeikis, R. (2011). On recursive parametric identification of Wiener systems. Information Technology and Control, 40(1), 21-28.
13. Pupeikis, R., Navakauskas, D., Ljung, L. (2003). Identification of Wiener systems with hard and discontinuous nonlinearities. Technical report LiTH-ISY-R-2501, Department of Electrical Engineering, Linköping University, SE-581 83 Linköping, Sweden.
14. Selmic, R.R., Lewis, F.L. (2000). Deadzone compensation in motion control systems using neural networks. IEEE Transactions on Automatic Control, 45(4), 602-613.
15. Selmic, R.R., Lewis, F.L. (2001). Neural net backlash compensation with Hebbian tuning using dynamic inversion. Automatica, 37, 1269-1277. (Pubitemid 32610257)
16. Selmic, R.R., Phoha, V.V., Lewis, F.L. Intelligent Compensation of Actuator Nonlinearities. http://www2.latech.edu/phoha/PDF.
17. Schoukens, J., Pintelon, R., Dobrowiecki, T., Rolain, Y. (2005). Identification of linear systems with nonlinear distortions. Automatica, 41, 491-504. (Pubitemid 40183245)
18. Widanage, J., Godfrey, K.R., Tan, A.H. (2004). System identification in the presence of a saturation nonlinearity. Journal of Electrical Engineering, 55(1-2), 46-49.
19. Vörö̈s, J. (2001). Parameter identification ofWiener systems with discontinuous nonlinearities. Systems & Control Letters, 44, 363-372. (Pubitemid 33034209)
20. Vörös, J. (2002). Modeling and parameter identification of systems with multisegment piecewise-linear characteristics. IEEE Trans. Automatic Control, 47(1), 184-188. (Pubitemid 34504342)
21. Vörös, J. (2010). Recursive identification of systems with noninvertible output nonlinearities. Informatica, 21(1), 139-148.
22. Vörös, J. (2010). Block-oriented nonlinear system identification. Lecture Notes in Control and Information Sciences, 404/2010, 35-51.
23. Vörös, J. (2011). Identification of nonlinear cascade systems with time-varying backlash. Journal of Electrical Engineering, 62(2), 87-92.
24. Wigren, T. (1993). Recursive prediction error identification using the nonlinear Wiener model. Automatica, 29(4), 1011-1025. (Pubitemid 23690867)