ON SENSITIVITY OF SOLUTIONS OF RICCATI EQUATIONS UNDER SMALL PARAMETER PERTURBATIONS AND OPTIMALITY IN LINEAR STOCHASTIC CONTROL SYSTEMS

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详细

We investigate sensitivity of solutions of Riccati equations under asymptotically small perturbations of their coefficients. Upper bound on the difference between solutions of algebraic and differential Riccati equations is derived. The result is applied to study optimality in the stochastic linear-quadratic control problem over an infinite time-horizon for an asymptotically autonomous system. We also treat an issue related to performance of invariant control strategy.

作者简介

E. Palamarchuk

Central Economic Mathematical Institute of RAS; National Research University Higher School of Economics

Email: e.palamarchuck@gmail.com
Moscow, Russia; Moscow, Russia

参考

  1. Квакернаак, X. Линейные оптимальные системы управления / Х. Квакернаак, Р. Сиван ; пер. с англ. под ред. В.А Васильева, Ю.А. Николаева — М. : Наука, 1977. — 650 c.
  2. Kwakernaak, H. and Sivan, R., Linear Optimal Control Systems, New York: Wiley-interscience, 1972.
  3. Dragan, V. Mathematical Methods in Robust Control of Linear Stochastic Systems / V. Dragan, T. Morozan, A.M. Stoica. — New York : Springer, 2006. — 324 p.
  4. Perturbation Theory for Matrix Equations / M. Konstantinov, D.W. Gu, V. Mehrmann, P. Petkov. — Amsterdam : Elsevier, 2003. — 524 p.
  5. Konstantinov, M.M. Sensitivity of the solutions to differential matrix Riccati equations / M.M. Konstantinov, G.B. Pelova // IEEE Trans. on Automatic Control. — 1991. — V. 36, № 2. — P. 213–215.
  6. Паламарчук, Е.С. Теорема сравнения для одного класса дифференциальных уравнений Риккати и её приложение / Е.С. Паламарчук // Дифференц. уравнения. — 2016. — Т. 52, № 8. — С. 1020–1025.
  7. Palamarchuk, E.S., Comparison theorem for a class of Riccati differential equations and its application, Differ. Equat., 2016, vol. 52, no. 8, pp. 981–986.
  8. Wang, B. Consensus of discrete-time multi-agent systems with decaying multiplicative uncertainties / B. Wang, Y.P. Tian // 2018 Chinese Automation Congress (CAC). — New York : IEEE, 2018. — P. 2247–2252.
  9. Design of autonomous cruise controller with linear time varying model / H.J. Chang, T.K. Yoon, H.C. Lee [et al.] // J. Electrical Engineering and Technology. — 2015. — V. 10, № 5. — P. 2162–2169.
  10. Models of continuous-time linear time-varying systems with fully adaptable system modes / M.A.G. De Anda, A.S. Reyes, R. Kaszynski, J. Piskorowski // New Approaches in Automation and Robotics / Ed. H. Aschemann. — Rijeka : IntechOpen, 2008. — P. 345–346.
  11. Zhang, H.Y. Explicit symplectic-precise iteration algorithms for linear quadratic regulator and matrix differential Riccati equation / H.Y. Zhang, J.Z. Luo, Y. Zhou // IEEE Access. — 2021. — V. 9. — P. 105424–105438.
  12. Адрианова, Л.В. Введение в теорию линейных систем дифференциальных уравнений / Л.В. Адрианова. — СПб. : Изд-во С.-Петерб. ун-та, 1992. — 239 c.
  13. Adrianova L., Introduction to Linear Systems of Differential Equations, Providence: American Mathematical Society, 1995.
  14. Harris, C.J. Some Aspects of Kinematic Similarity and the Stability of Linear Systems / C.J. Harris, J.F. Miles. — London : Academic Press, 1980. — 236 p.
  15. Паламарчук, Е.С. Асимптотическое поведение решения линейного стохастического дифференциального уравнения и оптимальность почти наверное для управляемого случайного процесса / Е.С. Паламарчук // Журн. вычислит. математики и мат. физики. — 2014. — Т. 54, № 1. — С. 89–103.
  16. Palamarchuk, E.S., Asymptotic behavior of the solution to a linear stochastic differential equation and almost sure optimality for a controlled stochastic process, Comput. Math. Math. Phys., 2014, vol. 54, pp. 83–96.
  17. Czornik, A. On time-varying LQG / A. Czornik // IFAC Proceedings Volumes. — 1998. — V. 31, № 18. — P. 411–415.
  18. On stability of linear time-varying second-order differential equations / L. Duc, A. Ilchmann, S. Siegmund, P. Taraba // Quarterly of Appl. Math. — 2006. — V. 64, № 1. — P. 137–151.
  19. Distributed gradient descent: nonconvergence to saddle points and the stable-manifold theorem / B. Swenson, R. Murray, H.V. Poor, S. Kar // 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton). — New York : IEEE, 2019. — P. 595–601.
  20. Ekman, T. Adaptive prediction of mobile radio channels utilizing a filtered random walk model for the coefficients / T. Ekman // Knowledge-Based Intelligent Information and Engineering Systems: 7th Int. Conf., KES 2003. Oxford, September 2003, Proceedings, Part I / Ed. V. Palade. — Berlin : Springer, 2011. — P. 1326–1333.
  21. Паламарчук, Е.С. О верхних функциях для интегральных квадратичных функционалов от процесса Орнштейна–Уленбека с переменными коэффициентами / Е.С. Паламарчук // Теория вероятностей и ее применения. — 2020. — Т. 65, № 1. — С. 23–41.
  22. Palamarchuk, E.S., On upper functions for integral quadratic functionals based on time-varying Ornstein–Uhlenbeck process, Theory of Probability & its Applications, 2020, vol. 65, no. 1, pp. 17–31.
  23. Белкина, Т.А. О стохастической оптимальности для линейного регулятора с затухающими возмущениями / Т.А. Белкина, Е.С. Паламарчук // Автоматика и телемеханика. — 2013. — № 4. — С. 110–128.
  24. Belkina, T.A. and Palamarchuk, E.S., On stochastic optimality for a linear controller with attenuating disturbances, Automat. Remote Contr., 2013, vol. 74, no. 4, pp. 628–641.
  25. Крамер, Г. Стационарные случайные процессы: свойства выборочных функций и их приложения / Г. Крамер, М. Лидбеттер ; пер. с англ. под. ред. Ю.А. Беляева — М. : Мир, 1969. — 398 c.
  26. Cramer, H. and Leadbetter, M.R., Stationary and Related Stochastic Processes: Sample Function Properties and their Applications, New York: Wiley, 1967.
  27. Song, I. Probability and Random Variables: Theory and Applications / I. Song, S.R. Park, S. Yoon. — Cham : Springer, 2022. — 505 p.

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