International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 6, No. 1, 8 Dec. 2013
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Structural Identification of Nonlinear Static System on Basis of Analysis Sector Sets
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Author(s)
Index Terms
Identification, Structure, Holder Condi-tion, Set, Secant, Virtual Portrait, Proximity
Abstract
Methods of structural identification of static systems with a vector input and several nonlinearities in the conditions of uncertainty are considered. We consider inputs irregular. The concept of structural space is introduced. In this space special structures (virtual portraits) are analyzed. The Holder condition is applied to construction of sector set, to which belongs a virtual portrait of system of identification. Criteria of decision-making on a class of nonlinear functions on the basis of the analysis of proximity of sector sets are described. Procedures of an estimation of structural parameters of two classes of nonlinearities are stated: power and a hysteresis.
Cite This Paper
Nikolay Karabutov, "Structural Identification of Nonlinear Static System on Basis of Analysis Sector Sets", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.1, pp.1-10, 2014. DOI:10.5815/ijisa.2014.01.01
Reference
[1]N.S. Raybman, and V.M. Chadeev. Construction of models of production processes. Energiya, Mos-cow, 1975.
[2]D. Graupe Identification of systems. Robert E. Krieger Publishing Co., Huntington, New York, 1999.
[3]L. Ljung. System identification – theory for the user (2nd ed.). Prentice-Hall, Upper Saddle River, New York, 1999.
[4]N.N. Karabutov. Adaptive identification of sys-tems: Information synthesis. Librokom, Moscow, 2006.
[5]M. Norgaard, O. Ravn, N.K. Poulsen, and L.K. Hansen. Neural networks for modelling and con-trol of dynamic systems: a practitioner's handbook. Springer-Verlag, London, 2001.
[6]J. Madár, J. Abonyi, and F. Szeifert. Genetic pro-gramming for the identification of nonlinear in-put−output models. Ind. Eng. Chem. Res., v44, 2005, pp.3178–3186.
[7]E. Righeto, L.H.M. Grassi, and J.A. Pereira. Non-linear plant identification by wavelets. In ABCM Symposium Series in Mechatronics, v1, 2004, pp.392-398.
[8]T. Sato, and M. Sato. Structural identification us-ing neural network and Kalman filter algorithms. Structural Eng./ Earthquake Eng., JSCE, v14, 1997, pp.23s -32s.
[9]S.F. Masri, J.P. Caffrey, T.K. Caughey, A.W. Smyth, and A.G. Chassiako. Direct Identification of the State Equation in Complex Nonlinear Sys-tems. In ICTAM04-Complex Nonlinear Systems, 2003, pp.1-2.
[10]L.A. Aguirre, M.F.S. Barroso, R.R. Saldanha, and A.M. Mendes. Imposing steady-state performance on identified nonlinear polynomial models by means of constrained parameter estimation. IЕЕE Proc. Conlrol Theory Appl., v151, 2004, pp.174-179.
[11]M. Espinoza, J.A.K. Suykens, and B. De Moor, Kernel based partially linear models and nonlinear identification. IEEE Transactions on Automatic Control, 50, 2005, pp.1602-1606.
[12]S.A. Billings, and Hua-Liang Wei. A new class of wavelet networks for nonlinear system identifica-tion. IEEE Transactions on neural networks, v16, 2005, pp.З62-874.
[13]N.N. Karabutov. About structures of state systems identification of static object with hysteresis. Int. J. Sensing, Computing and Control, v2, n2, 2012, pp.59-69.
[14]F. Mosteller, and J.W. Tukey. Data analysis and regression: A Second course in statistics. Reading, MA: Addison-Wesley, 1977.
[15]J. Johnston. Econometric methods (2nd ed.). McGraw-Hill Book Company, New York, 1972.
[16]N.R. Draper, and H. Smith. Applied Regression Analysis (3rd ed.) By John Wiley & Sons, Inc., 1998.
[17]A.G. Ivachnenko, and J.A. Muller. Selbstorganisa-tion von vorhersagemodellen. Veb Verlag Technik, Berlin, 1984.
[18]N.N. Karabutov. Structural identification of static objects: Fields, structures, methods. Librokom, Moscow, 2011.
[19]N.N. Karabutov. Decision-making on structure of univalent nonlinearities in system of structural identification of static systems. Int. J. Sensing, Computing and Control, v2, 2011, pp.103-110.
[20]N.N. Karabutov. Structures, fields and methods of identification of nonlinear static systems in the conditions of uncertainty. Intelligent control and automation, v1, n2, 2010, pp.59-67.
[21]E.G. Shilov. Mathematical analysis. Fizmathlit, Moscow, 1961.
[22]V.A. Efremovich, and A.K. Tolpygo. Geometry of proximity. FIMA, Moscow, 2007.
[23]A.B. Petrovsky. Space of sets and multisets. Edito-ral, URSS, Moscow, 2003.
[24]G. Choquet. L'Enseignement de la geometrie. Hermann, Paris, 1964.
[25]N.N. Karabutov. Structural identification of static processes with hysteresis nonlinearities in civil en-gineering. J. of Civil Engineering and Science, v1, n4, 2012, pp.22-29.
[26]Krasnoselskiy, M.A. and Pokrovsky, A.V. Systems with hysteresis. Nauka, Moscow, 1983.