A priori estimation of the minimal stabilization time for linear discrete-time systems with bounded control based on the apparatus of eigensets

6

Abstract

A linear system with discrete time and bounded control is considered. It is assumed that the system matrix is non-singular and diagonalizable, and the set of admissible control values is convex and compact. For a given system, the time-optimization problem is studied. In particular, it is required to construct a priori estimates of the optimal value of the minimal time as a function of the initial state and system parameters that do not require an exact construction of the class of null-controllable sets. To solve the problem, an apparatus of eigensets of a linear transformation is developed, and basic properties of non-trivial eigensets are formulated and proven. For the simplest case, when the set of admissible control values is a non-trivial eigenset of the system matrix, the response time function for a given initial state is constructed explicitly. For an arbitrary control system, a method is proposed for reducing to the simplest case by constructing internal and external approximations of a set of constraints on control values. Numerical calculations are presented demonstrating the efficiency and accuracy of the developed technique.

General Information

Keywords: linear system, discrete time, time-optimization problem, optimal control, a priori estimates of the optimal value of the objective function, eigenset

Journal rubric: Optimization Methods

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2025150106

Received: 13.01.2025

For citation: Guseva S.R., Ibragimov D.N. A priori estimation of the minimal stabilization time for linear discrete-time systems with bounded control based on the apparatus of eigensets. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2025. Vol. 15, no. 1, pp. 110–132. DOI: 10.17759/mda.2025150106. (In Russ., аbstr. in Engl.)

References

  1. Bellman R. Dinamicheskoye programmirovaniye [Dynamic programming]. Мoskva: IIL=Moscow: IIL., 1960. (In Russ.).
  2. Boltyanskij V.G. Matematicheskie metody optimal'nogo upravleniya [Mathematical methods of optimal control]. Мoskva: Nauka=Moscow: The science. 1969. (In Russ.).
  3. Boltyanskij V.G. Optimal’noe upravlenie diskretnymi sistemami [Optimal control of discrete systems]. Мoskva: Nauka=Moscow: The science. 1973. (In Russ.).
  4. Evtushenko Yu.G. Metody resheniya ekstremal'nyh zadach i ih prilozheniya v sistemah optimizacii [Methods for solving extreme problems and their applications in optimization systems]. Мoskva: Nauka=Moscow: The science. 1982. (In Russ.).
  5. Ibragimov D.N., Sirotin A.N. On the Problem of Optimal Speed for the Discrete Linear System with Bounded Scalar Control on the Basis of 0-controllability Sets // Autom. Remote Control. 2015. V. 76. No. 9. P. 1517–1540. DOI: 10.1134/S0005117919030019
  6. Ibragimov D.N., Sirotin A.N. On the Problem of Operation Speed for the Class of Linear Infinite-Dimensional Discrete-Time Systems with Bounded Control // Autom. Remote Control. 2017. V. 78. No. 10. P. 1731–1756. DOI: 10.1134/S0005117917100010
  7. Ibragimov D.N. On the Optimal Speed Problem for the Class of Linear Autonomous Infinite-Dimensional Discrete-Time Systems with Bounded Control and Degenerate Operator // Autom. Remote Control. 2019. V. 80. No. 3. P. 393–412. DOI: 10.1134/S0005117919030019.
  8. Ibragimov D.N., Novozhilin N.M., Portseva E.Yu. On Sufficient Optimality Conditions for a Guaranteed Control in the Speed Problem for a Linear Time-Varying Discrete-Time System with Bounded Control // Autom. Remote Control. 2021. V. 82. No. 12. P. 2076–2096. DOI: 10.31857/S0005231021120047
  9. Kolmogorov A.N., Fomin S.V. Elementy teorii funktsiy i funktsional'nogo analiza [Elements of the Theory of Functions and Functional Analysis]. Moskva: Nauka = Moscow: The science, 1981. (In Russ.)
  10. Moiseev N.N. Elementy teorii optimal'nykh sistem [Elements of the theory of optimal systems]. Мoskva: Nauka=Moscow: The science., 1975. (In Russ.).
  11. Pontryagin L.S., Boltyanskij V.G., Gamkrelidze R.V., Mishchenko B.F. Matematicheskaya teoriya optimal'nyh processov [Mathematical theory of optimal processes]. Мoskva: Nauka=Moscow: The science., 1969. (In Russ.).
  12. Propoi A.I. Elementy teorii optimal'nykh diskretnykh protsessov [Elements of the theory of optimal discrete processes]. Мoskva: Nauka=Moscow: The science. 1973. (In Russ.).
  13. Rokafellar R. Vypuklyy analiz [Convex Analysis] Мoskva: Mir=Moscow: Mir, 1973.
  14. Sirotin A.N., Formal’skii A.M. Reachability and Controllability of Discrete-Time Systems under Control Actions Bounded in Magnitude and Norm // Autom. Remote Control. 2003. V. 64. No. 12. P. 1844–1857. DOI: 10.1023/B:AURC.0000008423.93495.be
  15. Holtzman J.M., Halkin H. Directional convexity and the maximum principle for discrete systems // J. SIAM Control. V. 4. No. 2. 1966. P. 263–275. DOI: 10.1137/0304023
  16. Johnson C.R. Eigenset Generalizations of the Eigenvalue Concept // Journal of research of the National Bureau of Standards. V. 82. No. 2. P. 1977. 133–136. DOI: 10.6028/jres.082.013
  17. Kurzhanskiy A., Varaiya P. Ellipsoidal Techniques for Reachability Analysis of Discrete-Time Linear Systems // IEEE Transactions on Automatic Control. 2007. V. 52. No.1. P. 26–38. DOI: 10.1109/TAC.2006.887900
  18. Lin X. Zhang W. A maximum principle for optimal control of discrete-time stochastic Systems with multiplicative noise // IEEE Trans. Automatic Control. V. 60. No. 4. 2015. P. 1121–1126. DOI: 10.1109/TAC.2014.2345243
  19. Murota K. Eigensets and power products of a bimatroid // Advances in Mathematics. V. 80. No. 1. 1990. P. 78–91. DOI: 10.1016/0001-8708(90)90015-F
  20. Wang G., Yu Z. A Pontryagin's maximum principle for non-zero sum differential games of BSDEs with applications // IEEE Trans. Autom. Control. V. 55. No. 7. 2010. P. 1742–1754.
  21. Weibel C. Minkowski sums of polytopes: combinatorics and computation. Suisse: EPFL, 2007.
  22. Wu Z. A general maximum principle for optimal control of forward-backward stochastic systems // Automatica. V. 49. No. 5. 2013. P. 1473—1480.

Information About the Authors

Sofya R. Guseva, Student, Department of Probability Theory and Computer Modeling, Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-4625-7798, e-mail: son1522@yandex.ru

Danis N. Ibragimov, Candidate of Science (Physics and Matematics), Associate Professor of the Department of Probability Theory and Computer Modeling, Moscow Aviation Institute (national research university) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-7472-5520, e-mail: rikk.dan@gmail.com

Metrics

 Web Views

Whole time: 18
Previous month: 0
Current month: 18

 PDF Downloads

Whole time: 6
Previous month: 0
Current month: 6

 Total

Whole time: 24
Previous month: 0
Current month: 24