ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
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Proceedings of the Estonian Academy of Sciences. Physics. Mathematics
Algebraic formalism of differential one-forms for nonlinear control systems on time scales; 264-282
PDF | https://doi.org/10.3176/phys.math.2007.3.03

Authors
Zbigniew Bartosiewicz, Ülle Kotta ORCID Icon, Ewa Pawłuszewicz, Małgorzata Wyrwas
Abstract

The paper develops algebraic formalism of differential one-forms, associated with the nonlinear control system defined on homogeneous time scales. This formalism unifies the existing theories for continuous- and discrete-time systems. A field of meromorphic functions, corresponding to a control system, is introduced. It is equipped with two operators whose properties are studied. An inversive closure of this field is constructed with the aid of one-forms.

References

 1. Aulbach, B. and Hilger, S. Linear dynamic process with inhomogeneous time scale. In Nonlinear Dynamics and Quantum Dynamical Systems (Leonov, G., Reitmann, V. and Timmermann, W., eds), Math. Res., 1990, 59, 9–20.

  2. Hilger, S. Ein Mass kettenkalkülmit Anwendung auf Zentrumsmannigfaltigkeiten. PhD thesis, Universität Würzburg, 1988.

 3. Bohner, M. and Peterson, A. Dynamic Equations on Time Scales. Birkhäuser, Boston, 2001.
https://doi.org/10.1007/978-1-4612-0201-1

 4. Bartosiewicz, Z. and Pawłuszewicz, E. Dynamic feedback equivalence of nonlinear systems on time scales. In Proceedings of the 16th IFAC Congress, Prague, Czech Republic, July 3–8, 2005 (Piztek, P., ed.). Elsevier, Oxford, 2006.

 5. Bartosiewicz, Z. and Pawłuszewicz, E. Realization of linear control systems on time scale. Control Cybern., 2006, 35, 769–786.

 6. Fausett, L. V. and Murty, K. N. Controllability, observability and realizability criteria on time scale dynamical systems. Nonlinear Stud., 2004, 11, 627–638.

 7. Bartosiewicz, Z., Kotta, Ü. and Pawłuszewicz, E. Input-output and transfer equivalence of linear control systems on time scales. In Proceedings of the 11th IEEE International Conference on Methods and Models in Automation and Robotics (MMAR), 29 August–1 September 2005, Poland. 2005, 287–291.

 8. Kotta,Ü., Bartosiewicz, Z. and Pawłuszewicz, E. Equivalence of linear control systems on timescales. Proc. Estonian Acad. Sci. Phys. Math., 2006, 55, 43–52.
https://doi.org/10.3176/phys.math.2006.1.04

 9. Pawłuszewicz, E. and Bartosiewicz, Z. Linear control systems on time scales: unification of continuous and discrete. In Proceedings of the 10th IEEE International Conference on Methods and Models in Automation and Robotics 30 August–2 September 2004, Poland. 2004, 263–266.

10. Pawłuszewicz, E. and Bartosiewicz, Z. Unification of continuous-time and discrete-time systems: the linear case. In Proceedings of the 16th International Symposium on Mathematical Theory of Networks and Systems, MNTS2004, Leuver, Belgia. 2004.

11. Pawłuszewicz, E. and Bartosiewicz, Z. Realizability of linear control systems on time scales. In Proceedings of the 11th IEEE International Conference on Methods and Models in Automation and Robotics (MMAR), 29 August–1 September 2005, Poland. 2005, 293–298.

12. Yantir, A. Derivative and integration on time scale with Mathematica. In Proceedings of the 5th International Mathematica Symposium: Challenging the Boundaries of Symbolic Computation (Mitic, P., Ramsden, P. and Carne, J., eds). Imperial College Press, 2003, 325–331.
https://doi.org/10.1142/9781848161313_0042

13. Aranda-Bricaire, E., Kotta, Ü. and Moog, C. H. Linearization of discrete-time systems. SIAM J. Contr. Optim., 1996, 34, 1999–2023.
https://doi.org/10.1137/S0363012994267315

14. Moog, C. H., Conte, G. and Perdon, A. M. Nonlinear Control Systems: an Algebraic Setting. Lecture Notes in Control and Inform. Sci., 242. Springer, London, 1999.

15. Kotta, Ü., Zinober, A. S. I. and Liu, P. Transfer equivalence and realization of nonlinear higher order input-output difference equations. Automatica, 2001, 37, 1771–1778.
https://doi.org/10.1016/S0005-1098(01)00144-3

16. Bronstein, M. and Petkovšek, M. An introduction to pseudo-linear algebra. Theor. Comput. Sci., 1996, 157, 3–33.
https://doi.org/10.1016/0304-3975(95)00173-5

17. Halas, M. and Kotta, Ü. Pseudo-linear algebra: a powerful tool in unification of the study of nonlinear control systems. In Preprints of 7th IFAC Symposium on Nonlinear Control Systems, Pretoria, South Africa, 2007 (to appear).
https://doi.org/10.3182/20070822-3-ZA-2920.00117

18. Gürses, M., Guseinov, G. Sh. and Silindir, B. Integrable equations on time scales. J. Math. Phys., 2005, 46, 113510.
https://doi.org/10.1063/1.2116380

19. Grizzle, J. W. A linear algebraic framework for the analysis of discrete-time nonlinear systems. SIAM J. Control Optim., 1993, 31, 1026–1044.
https://doi.org/10.1137/0331046

20. Cohn, R. M. Difference Algebra. Wiley-Interscience, New York, 1965.

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