Identification of linear dynamic systems of fractional order with errors in variables based on an augmented system of equations

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Abstract

Equations with derivatives and fractional order differences are widely used to describe various processes and phenomena. Currently, methods of identification of systems described by equations with fractional order differences are actively developing. The paper is devoted to the identification of discrete dynamical systems described by equations with fractional order differences with errors in variables. The problems of identifying systems with errors in variables are often ill-conditioned. The paper proposes an algorithm that uses the representation of a normal biased system as an augmented equivalent system. This representation allows to reduce the number of conditionality of the problem to be solved. Test examples have shown that the proposed algorithm has a higher accuracy than the algorithms based on the decomposition of Cholesky and the minimization of the generalized Rayleigh quotient.

About the authors

Dmitriy V. Ivanov

Samara State Transport University

Author for correspondence.
Email: dvi85@list.ru
ORCID iD: 0000-0002-5021-5259
SPIN-code: 6672-4830
Scopus Author ID: 22937879800
ResearcherId: C-9460-2018
http://www.mathnet.ru/person42123

Cand. Phys. & Math. Sci.; Associate Professor; Dept. of Mechatronics, Automation, and Transport Control

2 V, Svobody st., Samara, 443066, Russian Federation

References

  1. Podlubny I. Fractional differential equations. An introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications, Mathematics in Science and Engineering, vol. 198. San Diego, Academic Press, 1999, xxiv+340 pp. https://doi.org/10.1016/s0076-5392(99)x8001-5
  2. Kilbas A. A., Srivastava H. M., Trujillo J. J. Theory and Applications of Fractional Differential Equations, North-Holland Mathematics Studies, vol. 204. Amsterdam, Elsevier, 2006, xx+523 pp. https://doi.org/10.1016/s0304-0208(06)x8001-5
  3. Uchaikin V. V. Heredity and nonlocality, In: Fractional Derivatives for Physicists and Engineers. Background and Theory, vol. 1, Nonlinear Physical Science. Berlin, Springer, 2013, pp. 3–58. https://doi.org/10.1007/978-3-642-33911-0_1
  4. Rabotnov Yu. N. Elements of Hereditary Solid Mechanics, Mir Publ., 1980, 388 pp.
  5. Slonimsky G. L. On the laws of deformation of real materials. I. The theories of Maxwell and Boltzmann, Acta Physicochim. URSS, 1940, vol. 12, pp. 99–128.
  6. Mainardi F. Fractional Calculus and Waves in Linear Viscoelasticity. An Introduction to Mathematical Models. Hackensack, NJ, World Scientific, 2010, xx+347 pp. https://doi.org/10.1142/p614
  7. Koeller R. C. Applications of fractional calculus to the theory of viscoelasticity, J. Appl. Mech., 1984, vol. 51, no. 2, pp. 299–307. https://doi.org/10.1115/1.3167616
  8. Boykov I. V., Krivulin N. P. Parametric identification of hereditary systems with distributed parameters, University Proceedings. Volga Region. Engineering Sciences, 2013, vol. 26, no. 2, pp. 120–129 (In Russian).
  9. Boykov I. V., Krivulin N. P. Recovery of the parameters of linear systems described by differential equations with variable coefficients, Meas. Tech., 2013, vol. 56, no. 4, pp. 359–356. https://doi.org/10.1007/s11018-013-0210-5
  10. Cois O., Oustaloup A., Battaglia E., Battaglia J.-L. Non integer model from modal decomposition for time domain system identification, IFAC Proc. Vol., 2000, vol. 33, no. 15, pp. 989–994. https://doi.org/10.1016/S1474-6670(17)39882-8
  11. Cois O., Oustaloup A., Poinot T., Battaglia J.-L. Fractional state variable filter for system identification by fractional model, In: 2001 European Control Conference (ECC) (4–7 Sept. 2001, Porto, Portugal), 2001, pp. 2481–2486. https://doi.org/10.23919/ECC.2001.7076300
  12. Malti R., Aoun M., Sabatier J., Oustaloup A. Tutorial on system identification using fractional differentiation models, IFAC Proc. Vol., 2006, vol. 39, no. 1, pp. 606–611. https://doi.org/10.3182/20060329-3-AU-2901.00093
  13. Ogorodnikov E. N., Radchenko V. P., Ungarova L. G. Mathematical modeling of hereditary elastically deformable body on the basis of structural models and fractional integrodifferentiation Riemann–Liouville apparatus, Vestn. Samar. Gos. Tekhn. Univ., Ser. Fiz.-Mat. Nauki [J. Samara State Tech. Univ., Ser. Phys. Math. Sci.], 2016, vol. 20, no. 1, pp. 167–194 (In Russian). https://doi.org/10.14498/vsgtu1456
  14. Ungarova L. G. The use of linear fractional analogues of rheological models in the problem of approximating the experimental data on the stretch polyvinylchloride elastron, Vestn. Samar. Gos. Tekhn. Univ., Ser. Fiz.-Mat. Nauki [J. Samara State Tech. Univ., Ser. Phys. Math. Sci.], 2016, vol. 20, no. 4, pp. 691–706 (In Russian). https://doi.org/10.14498/vsgtu1523
  15. Lewandowski R., Chorążyczewski B. Identification of the parameters of the Kelvin–Voigt and the Maxwell fractional models, used to modeling of viscoelastic dampers, Comp. Struct., 2009, vol. 88, no. 1–2, pp. 1–17. https://doi.org/10.1016/j.compstruc.2009.09.001
  16. Shabani R., Jahani K., Di Paola M., Sadeghi M. N. Frequency domain identification of the fractional Kelvin–Voigt’s parameters for viscoelastic materials, Mech. Mater., 2019, vol. 137,103099. https://doi.org/10.1016/j.mechmat.2019.103099
  17. Söderström T. Errors-in-Variables Methods in System Identification, Communications and Control Engineering. Cham, Switzerland, Springer, 2018, xxvii+485 pp. https://doi.org/10.1007/978-3-319-75001-9.
  18. Chetoui M., Malti R., Thomassin M., Aoun M., Najar S., Oustaloup A., Abdelkrim M.N. EIV methods for system identification with fractional models, IFAC Proceedings Volumes, 2012, vol. 45, no. 16, pp. 1641–1646. https://doi.org/10.3182/20120711-3-BE-2027.00270
  19. Chetoui M., Thomassin M., Malti R., Aoun M., Najar S., Abdelkrim M. N., Oustaloup A. New consistent methods for order and coefficient estimation of continuous-time errors-in-variables fractional models, Comp. Math. Appl., 2013, vol. 66, no. 5, pp. 860–872. https://doi.org/10.1016/j.camwa.2013.04.028
  20. Ivanov D. V. Identification discrete fractional order linear dynamic systems with errors-in-variables, In: East-West Design and Test Symposium (EWDTS 2013) (27–30 Sept. 2013, Rostov on Don, Russia), 2013, pp. 374–377. https://doi.org/10.1109/EWDTS.2013.6673122
  21. Ivanov D. V. Estimation of parameters of linear fractional order ARX systems with noise in the input signal, Tomsk State University Journal of Control and Computer Science, 2014, no. 2(27), pp. 30–38 (In Russian).
  22. Ivanov D. V., Ivanov A. V. Identification fractional linear dynamic systems with fractional errors-in-variables, J. Phys.: Conf. Ser., 2017, vol. 803, 012058. https://doi.org/10.1088/1742-6596/803/1/012058
  23. Zhdanov A. I., Shamarov P. A. A direct projection method in the problem of complete least squares, Autom. Remote Control, 2000, vol. 61, no. 4, pp. 610–620.
  24. Granger C. W. J., Joyeux R. An introduction to long-memory time series models and fractional differencing, J. Time Series Anal., 1980, vol. 1, no. 1, pp. 15–29. https://doi.org/https://doi.org/10.1111/j.1467-9892.1980.tb00297.x
  25. Hosking J. R. M. Fractional differencing, Biometrika, 1981, vol. 68, no. 1, pp. 165–176. https://doi.org/10.1093/biomet/68.1.165
  26. Sierociuk D., Dzieliński A. Fractional Kalman filter algorithm for the states parameters and order of fractional system estimation, Int. J. Appl. Math. Comput. Sci., 2006, vol. 16, no. 1, pp. 129–140.
  27. Djouambai A., Voda A., Charef A. Recursive prediction error identification of fractional order models, Commun. Nonlinear Sci. Numer. Simulat., 2012, vol. 17, no. 6, pp. 2517–2524. https://doi.org/10.1016/j.cnsns.2011.08.015
  28. Dzieliński A., Sierociuk D. Some applications of fractional order calculus, Bull. Polish Acad. Sci. Tech. Sci., 2010, vol. 58, no. 4, pp. 583–592. https://doi.org/10.2478/v10175-010-0059-6
  29. Ivanov D. V., Ivanov A. V., Sandler I., Chertykovtseva N. V. Identification of the heating model plastic injection molding machines, Zhurnal SVMO, 2017, vol. 19, no. 3, pp. 82–89 (In Russian). https://doi.org/10.15507/2079-6900.19.201703.82-90
  30. Ostalczyk P. Discrete Fractional Calculus. Applications in Control and Image Processing, Series in Computer Vision, vol. 4. Hackensack, NJ, World Scientific, 2016, xxxi+361 pp. https://doi.org/10.1142/9833
  31. Mozyrska D., Wyrwas M. Stability of discrete fractional linear systems with positive orders, IFAC-PapersOnLine, 2017, vol. 50, no. 1, pp. 8115–8120. https://doi.org/10.1016/j.ifacol.2017.08.1250
  32. Wilkinson J. H. The Algebraic Eigenvalue Problem, Monographs on Numerical Analysis. Oxford Science Publications. Oxford, Clarendon Press, 1988, xviii+682 pp.
  33. Zhdanov A. I. The solution of ill-posed stochastic linear algebraic equations by the maximum likelihood regularization method, U.S.S.R. Comput. Math. Math. Phys., 1988, vol. 28, no. 5, pp. 93–96. https://doi.org/10.1016/0041-5553(88)90014-6

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