Piezoelectric Transducer Modeling: with System Identification (SI) Method
System identification is the process of creating
models of dynamic process from input- output signals. The aim of
system identification can be identified as “ to find a model with
adjustable parameters and then to adjust them so that the predicted
output matches the measured output". This paper presents a method
of modeling and simulating with system identification to achieve the
maximum fitness for transformation function. First by using
optimized KLM equivalent circuit for PVDF piezoelectric transducer
and assuming different inputs including: sinuside, step and sum of
sinusides, get the outputs, then by using system identification
toolbox in MATLAB, we estimate the transformation function from
inputs and outputs resulted in last program. Then compare the fitness
of transformation function resulted from using ARX,OE(Output-
Error) and BJ(Box-Jenkins) models in system identification toolbox
and primary transformation function form KLM equivalent circuit.
[1] (Flynn and Sanders) Flynn, A.M.; Sanders, S.R. 2002." Fundamental
limits on energy transfer and circuit considerations for piezoelectric
transformers". IEEE Transactions on Power Electronics, vol.17, (no.1),
IEEE, Jan. 2002. p.-14.
[2] (Ikeda1990)Ikeda.T "Fundamentals of piezoelectricity", Oxford
University Press.
[3] R.L.Lin, F. C. Lee, and E. Baker, " Characterization of piezoelectric
transformers" in Proc, IEEE VPEC, 2000, pp. 219-225.
[4] S. Nitin, "Introduction of System Identification",DOI=
http://www.Tataelxsi.co.in
[5] Lennart Ljung , "Nonlinear Black-Box Modeling in System
Identification". Dept of Electrical Engineering , Linkoping University,
Sweden.2001.
[6] R. Haber and L. Keviczky , " Nonlinear system identification - inputoutput
modeling approach, Vol 1 and 2. Kluwer Academic Publisher
(2004 ) 901-903.
[7] J.S. Lew, J.N.Juang and R.W. Longman. "Comparison of Several
System Identification Methods for Flex─▒ble Structures", NASA
Technical Memorandum, March 1991.
[8] A. Juditsku, H. Hjalmarsson, A. Benveniste, B. Deylon,L. Ljung,
J.Sjoberg, and Q.Zhang." Nonlinear black-box modeling in system
identification: Mathematical foundations," Automatics, 31, 1995.
[9] MATLAB Toolbox
[1] (Flynn and Sanders) Flynn, A.M.; Sanders, S.R. 2002." Fundamental
limits on energy transfer and circuit considerations for piezoelectric
transformers". IEEE Transactions on Power Electronics, vol.17, (no.1),
IEEE, Jan. 2002. p.-14.
[2] (Ikeda1990)Ikeda.T "Fundamentals of piezoelectricity", Oxford
University Press.
[3] R.L.Lin, F. C. Lee, and E. Baker, " Characterization of piezoelectric
transformers" in Proc, IEEE VPEC, 2000, pp. 219-225.
[4] S. Nitin, "Introduction of System Identification",DOI=
http://www.Tataelxsi.co.in
[5] Lennart Ljung , "Nonlinear Black-Box Modeling in System
Identification". Dept of Electrical Engineering , Linkoping University,
Sweden.2001.
[6] R. Haber and L. Keviczky , " Nonlinear system identification - inputoutput
modeling approach, Vol 1 and 2. Kluwer Academic Publisher
(2004 ) 901-903.
[7] J.S. Lew, J.N.Juang and R.W. Longman. "Comparison of Several
System Identification Methods for Flex─▒ble Structures", NASA
Technical Memorandum, March 1991.
[8] A. Juditsku, H. Hjalmarsson, A. Benveniste, B. Deylon,L. Ljung,
J.Sjoberg, and Q.Zhang." Nonlinear black-box modeling in system
identification: Mathematical foundations," Automatics, 31, 1995.
[9] MATLAB Toolbox
@article{"International Journal of Electrical, Electronic and Communication Sciences:52800", author = "Nora Taghavi and Ali Sadr", title = "Piezoelectric Transducer Modeling: with System Identification (SI) Method", abstract = "System identification is the process of creating
models of dynamic process from input- output signals. The aim of
system identification can be identified as “ to find a model with
adjustable parameters and then to adjust them so that the predicted
output matches the measured output". This paper presents a method
of modeling and simulating with system identification to achieve the
maximum fitness for transformation function. First by using
optimized KLM equivalent circuit for PVDF piezoelectric transducer
and assuming different inputs including: sinuside, step and sum of
sinusides, get the outputs, then by using system identification
toolbox in MATLAB, we estimate the transformation function from
inputs and outputs resulted in last program. Then compare the fitness
of transformation function resulted from using ARX,OE(Output-
Error) and BJ(Box-Jenkins) models in system identification toolbox
and primary transformation function form KLM equivalent circuit.", keywords = "PVDF modeling, ARX, BJ(Box-Jenkins),
OE(Output-Error), System Identification.", volume = "2", number = "3", pages = "380-6", }