Piezoelectric Transducer Modeling: with System Identification (SI) Method

Authors: Nora Taghavi, Ali Sadr

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.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330775

References:

[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