International Journal of Intelligent Systems and Applications(IJISA)
ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)
Published By: MECS Press
IJISA Vol.7, No.9, Aug. 2015
Structural Identification of Nonlinear Dynamic Systems
Full Text (PDF, 603KB), PP.1-11
The method of structural identification nonlinear dynamic systems is offered in the conditions of uncertainty. The method of construction the set containing the data about a nonlinear part of system is developed. The concept of identifiability system for a solution of a problem structural identification is introduced. The special class of structures S for a solution of problem identification is introduced. We will show that the system is identified, if the structure S is closed. The method of estimation the class of nonlinear functions on the basis of the analysis sector sets for the offered structure S is described. We showed, as on S a preliminary conclusion about a form of nonlinear function to make. We offer algorithms of structural identification of single-valued and many-valued nonlinearities. Examples of structural identification of nonlinear systems are considered.
Cite This Paper
Nikolay Karabutov,"Structural Identification of Nonlinear Dynamic Systems", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.9, pp.1-11, 2015. DOI: 10.5815/ijisa.2015.09.01
V.G. Shashiashvili, “Structural identification of nonlinear dynamic systems on set of the continuous block-oriented models,” in XII All-Russia conference on problems of con-trol ARCPC-2014. Moscow on June, 16-19th, 2014. Mos-cow: V.A. Trapeznikov Institute of Control Sciences, 2014, pp. 3018-3028.
T.H.Van Pelt, and D.S. Bernstein, “Nonlinear system iden-tification using Hammerstein and non-linear feedback models with piecewise linear static maps,” International journal control, 2001, vol. 74, no. 18, pp. 1807-1823.
W.J. Rugh, Nonlinear system theory: The Volterra/Wiener approach, The Johns Hopkins University Press, 1981.
G. Dimitriadis, Investigation of nonlinear aeroelastic sys-tems. Thesis of degree the doctor of philosophy. University of Manchester, 2001.
G. Kerschen, K. Worden, A.F. Vakakis, and J.C. Golinval, “Past, present and future of nonlinear system identification in structural dynamics,” Mechanical systems and signal processing, 2006, vol. 20, pp. 505–592.
R.Lin, and D.J. Ewins, “Location of localized stiffness non-linearity using measured modal data,” Mechanical systems and signal processing, 1995, vol. 9, pp. 329-339.
C.P. Fritzen, “Damage detection based on model updating methods,” Mechanical systems and signal processing, 1998, vol. 12, pp. 163-186.
R. Pascual, I. Trendafilova, J.C. Golinval, and W. Heylen, “Damage detection using model updating and identification techniques,” in Proceedings of the Second International Conference on Identification in Engineering Systems, Swansea, 1999.
I. Trendafilova, V. Lenaerts, G. Kerschen, J.C. Golinval, J.C., and H. Van Brussel, “Detection, localization and identification of nonlinearities in structural dynamics,” in: Proceedings of the International Seminar on Modal Analy-sis (ISMA), Leuven, 2000.
P. Atkins, and K. Worden, “Identification of a multi-degree-of-freedom nonlinear system,” in Proceedings of the 15th International Modal Analysis, Conference, Orlando, 1997, pp. 1023-1028.
J.S. Bendat, A.G. Piersol, Random Data: Analysis and Measurement Procedures, third ed. Wiley Interscience: New York, 2000.
G. Kerschen, J.C. Golinval, and F.M. Hemez, “Bayesian model screening for the identification of non-linear me-chanical structures,” Journal of vibration and acoustics, vol. 125, pp. 389–397, 2003.
Y. Fan, and C.J. Li, “Non-linear system identification using lumped parameter models with embedded feedforward neural networks,” Mechanical systems and signal pro-cessing, 2002, vol. 16, pp.357–372.
M. Peifer, J. Timmer, and H.U. Voss, “Nonparametric identification of nonlinear oscillating systems,” Journal of sound and vibration, 2003, vol. 267, pp. 1157–1167.
H. Yu, J. Peng, and Y. Tang, “Identification of Nonlinear Dynamic Systems Using Hammerstein-Type Neural Net-work,” Mathematical problems in engineering, 2014, vol. 2014, article ID 959507.
A.W. Smith A.W., S.F. Masri, E.B. Kosmatopoulos, A.G. Chassiakos, and T.K. Caughey, “Development of adaptive modeling techniques for non-linear hysteretic systems,” In-ternational journal of non-linear mechanics, 2002, vol. 37, is. 8, pp. 1435-1451.
J. Vörös, “Modeling and identification of hysteresis using special forms of the Coleman–Hodgdon model,” Journal of electrical engineering, 2009, vol. 60, no. 2, pp. 100–105.
K. Worden, G. Manson, “On the identification of hysteretic systems, Part I: an extended evolutionary scheme,” in Pro-ceedings of the IMAC-XXVIII February 1–4, 2010, Jack-sonville, Florida USA. 2010,9p.
M. Peimani, M.J. Yazdanpanah, and N. Khaji, “Parameter estimation in hysteretic systems based on adaptive least-squares,” Journal of information systems and telecommu-nication, 2013, vol. 1, no. 4, pp. 217-221.
Y. Tan, R. Dong, H. Chen, and H. He, “Neural network based identification of hysteresis in human meridian sys-tems,” Int. J. Appl. Math. Comput. Sci., 2012, vol. 22, no. 3, pp. 685–694.
Y. Ding, B.Y. Zhao, and B. Wu, “Structural system identi-fication with extended Kalman filter and orthogonal de-composition of excitation,” mathematical problems in en-gineering, 2014, vol., article ID 987694, 10 p.
N.N. Karabutov, “Selection of the structure of a model in processing the results of measurements in control systems,” Measurement techniques, 2008,vol. 51, no. 9, pp. 960-966.
N.N. Karabutov, Structural Identification of Systems. Analysis of Information Structures. Moscow: URSS/ Librokom, 2009.
N.N. Karabutov, Structural identification of static objects: Fields, structures, methods. Moscow: Librokom, 2011.
N.N. Karabutov, “Structural identification of nonlinear static system on basis of analysis sector sets,” International journal of intelligent systems and applications, 2014, vol. 6, no. 1. pp. 1-10.
V.S. Pugachev, Automatic control fundamentals. Moscow: Nauka, 1968.
Y.E. Kazakov, B.G. Dostupov, Statistical dynamics of nonlinear automatic systems. Moscow: Fizmatgis, 1962.
V.D. Furasov, Stability of motion, estimation and stabiliza-tion. Moscow: Nauka, 1977.
Choquet G. L'enseignement de la geometrie. Paris: Her-mann, 1964.
N.N. Karabutov, Method of structural identification non-linear plants. Saarbrucken: Palmarium Academic Publishing, 2014.
F. Mosteller, and J. Tukey, Data analysis and regression: A second course in statistics. Addison-Wesley Publishing Company. 1977.
M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science, 1989.