Design of Suboptimal Robust Controllers Based on a Priori and Experimental Data

封面

如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

This paper develops a novel unified approach to designing suboptimal robust control laws for uncertain objects with different criteria based on a priori information and experimental data. The guaranteed estimates of the γ0, generalized H2, and H∞ norms of a closed loop system and the corresponding suboptimal robust control laws are expressed in terms of solutions of linear matrix inequalities considering a priori knowledge and object modeling data. A numerical example demonstrates the improved quality of control systems when a priori and experimental data are used together.

作者简介

M. Kogan

Nizhny Novgorod State University of Architecture and Civil Engineering

Email: mkogan@nngasu.ru
Nizhny Novgorod, Russia

A. Stepanov

Nizhny Novgorod State University of Architecture and Civil Engineering

编辑信件的主要联系方式.
Email: andrey8st@yahoo.com
Nizhny Novgorod, Russia

参考

  1. Поляк Б.Т., Щербаков П.С. Робастная устойчивость и управление. М.: Наука, 2002.
  2. Petersen I.R., Tempo R. Robust Control of Uncertain Systems: Classical Results and Recent Developments // Automatica. 2014. V. 50. No. 5. P. 1315-1335.
  3. Андриевский Б.Р., Фрадков А.Л. Метод скоростного градиента и его приложения // АиТ. 2021. № 9. С. 3-72.
  4. Annaswamy A.A., Fradkov A.L. A Historical Perspective of Adaptive Control and Learning // Annual Reviews in Control. 2021. V. 52. P. 18-41.
  5. De Persis C., Tesi P. Formulas for Data-Driven Control: Stabilization, Optimality and Robustness // IEEE Trans. Automat. Control. 2020. V. 65. No. 3. P. 909-924.
  6. Waarde H.J., Eising J., Trentelman H.L., Camlibel M.K. Data Informativity: a New Perspective on Data-Driven Analysis and Control // IEEE Trans. Automat. Control. 2020. V. 65. No. 11. P. 4753-4768.
  7. Berberich J., Koch A., Scherer C.W., Allgower F. Robust data-driven state-feedback design // Proc. Amer. Control Conf. 2020. P. 1532-1538.
  8. Waarde H.J., Camlibel M.K., Mesbahi M. From Noisy Data to Feedback Controllers: Nonconservative Design via a Matrix S-Lemma // IEEE Trans. Automat. Control. 2022. V. 67. No. 1. P. 162-175.
  9. Biso A., De Persis C., Tesi P. Data-driven Control via Petersen's Lemma // Automatica. 2022. V. 145. Article 110537.
  10. Willems J.C., Rapisarda P., Markovsky I., De Moor B. A note on persistency of excitation // Syst. Control Lett. 2005. V. 54. P. 325-329.
  11. Якубович В.А. S-процедура в нелинейной теории управления // Вестник Ленинградского университета. Математика. 1977. Т. 4. С. 73-93.
  12. Petersen I.R. A stabilization algorithm for a class of uncertain linear systems // Syst. Control Lett. 1987. V. 8. P. 351-357.
  13. Doyle J.C. Analysis of feedback systems with structured uncertainties // IEE Proc. 1982. V. 129. Part D(6). P. 242-250.
  14. Safonov M.G. Stability margins of diagonally perturbed multivariable feedback systems // IEE Proc. 1982. V. 129. Part D(6). P. 251-256.
  15. Kogan M.M. Optimal discrete-time H∞/γ0 ltering and control under unknown covariances // Int. J. Control. 2016. V. 89. No. 4. P. 691-700.
  16. Wilson D.A. Convolution and Hankel Operator Norms for Linear Systems // IEEE Trans. Autom. Control. 1989. V. 34. No. 1. P. 94-97.
  17. Баландин Д.В., Бирюков Р.С., Коган М.М. Минимаксное управление уклонениями выходов линейной дискретной нестационарной системы // АиТ. 2019. № 12. С. 3-24.
  18. Boyd S., Vandenberghe L. Convex Optimization. Cambridge: University Press, 2004.

版权所有 © The Russian Academy of Sciences, 2023

##common.cookie##