Dynamics, Information and Control in Physical Systems

  • Alexander L. Fradkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3457)


The subject and methodology of an emerging field related to physics, control theory and indormation theory are outlined. The paradigm of cybernetical physics as studying physical systems by cybernetical means is discussed. Examples of transformation laws describing excitability properties of dissipative and bistable systems are presented. A possibility of application to analysis and design of information transmission systems and complex networks is discussed.


Physical System Goal Function Excitability Index Control Goal Small Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Landauer, R.: The physical nature of information. Phys. Lett. A. 217, 188–193 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Shannon, C.: A Mathematical Theory of Communication. Bell Syst. Tech. J. 27(3), 379–423 (1948); 4, 623-656 zbMATHMathSciNetGoogle Scholar
  3. 3.
    von Neumann, J.: Theory of Self-Reproducing Automata. In: Edited and completed by Burks, W. (ed.) Theory of Self-Reproducing Automata. University Illinois Press, Urbana and London (1966)Google Scholar
  4. 4.
    Landauer, R.: Irreversibility and heat generation in the computing process. IBM J. Res. Develop 3, 183–191 (1961)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Landauer, R.: Energy Requirements in Communication. Appl. Phys. Lett. 51, 2056–2058 (1987)CrossRefGoogle Scholar
  6. 6.
    Landauer, R.: Minimal Energy Requirements in Communication. Science 272, 1914–1918 (1996)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Norton, J.D.: Eaters of the Lotus: Landauer’s Principle and the Return of Maxwell’s Demon, PHIL-SCI 1729,
  8. 8.
    Bartsev, S.I., Okhonin, V.A.: Adaptive networks of information processing. Krasnoyarsk, Inst. of Physics SO AN SSSR (1986) (In Russian) Google Scholar
  9. 9.
    Brockett, R.W.: Control theory and analytical mechanics. In: Martin, C., Hermann, R. (eds.) Geometric Control Theory, Lie Groups. V. VII, pp. 1–48. Mat. Sci. Press, Brookine (1977)Google Scholar
  10. 10.
    Ott, T., Grebogi, C., Yorke, G.: Controlling chaos. Phys. Rev. Lett. 64, 1196–1199 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Fradkov, A.L., Yu, P.A.: Introduction to control of oscillations and chaos. World Scientific, Singapore (1998)zbMATHCrossRefGoogle Scholar
  12. 12.
    Fradkov, A.L.: Exploring nonlinearity by feedback. Physica D. 128(2-4), 159–168 (1999)zbMATHCrossRefGoogle Scholar
  13. 13.
    Fradkov, A.L.: Investigation of physical systems by means of feedback. Autom. Remote Control 60(3), 3–22 (1999)MathSciNetGoogle Scholar
  14. 14.
    Fradkov, A.L.: Cybernetical physics, Nauka, St.Petersburg, p. 208 (2003) (In Russian)Google Scholar
  15. 15.
    Vorotnikov, V.I.: Partial Stability and Control. Birkhäuser, Basel (1998)zbMATHGoogle Scholar
  16. 16.
    Fradkov, A., Miroshnik, I.V., Nikiforov, V.O.: Nonlinear and adaptive control of complex systems. Kluwer Academic Publishers, Dordrecht (1999)zbMATHGoogle Scholar
  17. 17.
    Krstić, M., Kanellakopoulos, I., Kokotović, P.V.: Nonlinear and Adaptive Control Design, New York. Wiley, Chichester (1995)Google Scholar
  18. 18.
    Zhou, K., Doyle, J.C., Glover, K.: Robust and Optimal Control. Prentice Hall, Englewood Cliffs (1996)zbMATHGoogle Scholar
  19. 19.
    Shiriaev, A.S., Fradkov, A.L.: Stabilization of invariant sets for nonlinear systems with application to control of oscillations. Intern. J. of Robust and Nonlinear Control 11, 215–240 (2001)CrossRefMathSciNetGoogle Scholar
  20. 20.
    Chernousko, F.L.: Some problems of optimal control with a small parameter. J. Appl. Math. Mech. 3, 12–22 (1968)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Stewart, H.B., Thompson, J.M.T., Ueda, U., Lansbury, A.N.: Optimal escape from potential wells – patterns of regular and chaotic bifurcations. Physica D. 85, 259–295 (1995)zbMATHCrossRefMathSciNetGoogle Scholar
  22. 22.
    DeMarco, C.L.: A phase transition model for cascading network failure. IEEE Control Systems Magazine 21(6), 40–51 (2001)CrossRefGoogle Scholar
  23. 23.
    Law, S., Paganini, F., Doyle, J.: Internet congestion control. IEEE Control Systems Magazine 22(1), 28–43 (2002)CrossRefGoogle Scholar
  24. 24.
    Wen, J.T., Arcak, M.: A unifying passivity framework for network flow control. IEEE Trans. Autom. Contr. AC-49(2), 162–174 (2004)CrossRefMathSciNetGoogle Scholar
  25. 25.
    Special Issue on Networked Control Systems. In: Antsaklis, P., Baillieul, J. (eds.) IEEE Trans. Autom. Contr., vol. AC-49(9) (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alexander L. Fradkov
    • 1
  1. 1.Institute for Problems of Mechanical Engineering of RASSt.PetersburgRussia

Personalised recommendations