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A spectral method of the analysis of linear control systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A spectral method of the analysis of linear control systems is considered. Within the framework of this approach the σ-entropy of input signals and the σ-entropy norm of systems are introduced. The invariance of the introduced norm makes it possible to get invariant results of σ-entropy analysis.
Rocznik
Strony
667--679
Opis fizyczny
Bibliogr. 30 poz., wykr.
Twórcy
  • Institute of Control Sciences, Russian Academy of Sciences, 65 Profsoyuznaya Street, Moscow, Russia
  • Institute of Control Sciences, Russian Academy of Sciences, 65 Profsoyuznaya Street, Moscow, Russia, v.boichenko@gmail.com
Bibliografia
  • [1] Belov, A.A. and Andrianova, O.G. (2016). Anisotropy-based suboptimal state-feedback control design using linear matrix inequalities, Automation and Remote Control 77(10): 1741–1755.
  • [2] Belov, A.A. Andrianova, O.G. and Kurdyukov, A.P. (2018). Control of Discrete-Time Descriptor Systems, Springer, Cham.
  • [3] Bertsekas, D.P. (2003). Convex Analysis and Optimization, Athena Scientific, Nashua, NH.
  • [4] Boichenko, V.A. (2017). Anisotropy-based analysis for case of nonzero initial condition, Large-Scale Systems Control (67): 32–51.
  • [5] Boichenko, V.A. and Belov, A.A. (2017). On stochastic gain of linear systems with nonzero initial condition, 25th Mediterranean Conference on Control and Automation, MED 2017, Valletta, Malta, pp. 817–821.
  • [6] Boichenko, V.A. and Kurdyukov, A.P. (2016). On lower bound of anisotropic norm, IFAC-PapersOnLine 49(13): 48–52.
  • [7] Boichenko, V.A. and Kurdyukov, A.P. (2017). On lower bound of anisotropic norm of the linear stochastic system, Automation and Remote Control 78(4): 643–653.
  • [8] Boyd, S. and Vandenberghe, L. (2004). Convex Optimization, Cambridge University Press, Cambridge.
  • [9] Cover, T.M. and Thomas, J.A. (1991). Elements of Information Theory, Wiley, New York, NY.
  • [10] Diamond, P., Vladimirov, I.G., Kurdyukov, A.P. and Semyonov, A.V. (2001). Anisotropy-based performance analysis of linear discrete time invariant control systems, International Journal of Control 74(1): 28–42.
  • [11] Gantmacher, F.R. (2000). The Theory of Matrices, AMS, Providence, RI.
  • [12] Iglesias, P.A. and Mustafa, D. (1993). State-space solution of the discrete-time minimum entropy control problem via separation, IEEE Transactions on Automatic Control 38(10): 1525–1530
  • [13] Iglesias, P.A., Mustafa, D. and Glover, K. (1990). Discrete-time H∞ controllers satisfying a minimum entropy criterion, Systems & Control Letters 14(4): 275–286.
  • [14] Kurdyukov, A.P. Kustov, A. Yu. Tchaikovsky, M.M. and Karny, M. (2013). The concept of mean anisotropy of signals with nonzero mean, 19th International Conference on Process Control, Štrbské Pleso, Slovakia, pp. 37–41.
  • [15] Kurdyukov, A.P. and Maximov, E.A. (2005). State-space solution to stochastic H∞-optimization problem with uncertainty, 16th IFAC World Congress, Prague, Czech Republic, pp. 429–434.
  • [16] Kurdyukov, A.P., Maximov, E.A. and Tchaikovsky, M.M. (2006). Homotopy method for solving anisotropy-based stochastic H∞-optimization problem with uncertainty, 5th IFAC Symposium on Robust Control Design, Toulouse, France, pp. 327–332.
  • [17] Kustov, A. Yu. (2014). Anisotropy-based analysis and synthesis problems for input disturbances with nonzero mean, 15th International Carpathian Control Conference, ICCC-2014, Velké Karlovice, Czech Republic, pp. 291–295.
  • [18] Kustov, A. Yu., Kurdyukov, A.P. and Yurchenkov, A.V. (2016). On the anisotropy-based bounded real lemma formulation for the systems with disturbance-term multiplicative noise, IFAC-PapersOnLine 49(13): 65–69.
  • [19] Kwakernaak, H. and Sivan, R. (1972). Linear Optimal Control Systems, Wiley, New York, NY.
  • [20] Mustafa, D. and Glover, K. (1990). Minimum Entropy H∞ Control, Springer, Berlin/Heidelberg.
  • [21] Poznyak, A.S. (2008). Advanced Mathematical Tools for Automatic Control Engineers, Vol. 1: Deterministic Techniques, Elsevier, Amsterdam.
  • [22] Rockafellar, R.T. (1970). Convex Analysis, Princeton University Press, Princeton.
  • [23] Semyonov, A.V., Vladimirov, I.G. and Kurdyukov, A.P. (1994). Stochastic approach to H∞-optimization, 33rd IEEE Conference on Decision and Control, Lake Buena Vista, FL, USA, pp. 2249–2250.
  • [24] Tchaikovsky, M.M. and Timin, V.N. (2017). Synthesis of anisotropic suboptimal control for linear time-varying systems on finite time horizon, Automation and Remote Control 78(7): 1203–1217.
  • [25] Timin, V.N. and Kurdyukov, A.P. (2015). Anisotropy-based multicriteria time-varying filtering on finite horizon, Doklady Mathematics 92(2): 638–642.
  • [26] Timin, V.N. and Kurdyukov, A.P. (2016). Suboptimal anisotropic filtering in a finite horizon, Automation and Remote Control 77(1): 1–20.
  • [27] Vladimirov, I.G., Kurdyukov, A.P., Maksimov, E.A. and Timin, V.N. (2005). Anisotropy-based control theory—the new approach to stochastic robust control theory, 4th International Conference on System Identification and Control Problems, SICPRO‘05, Moscow, Russia, pp. 29–94.
  • [28] Yurchenkov, A.V., Kustov, A. Yu. and Kurdyukov, A.P. (2016). Anisotropy-based bounded real lemma for discrete-time systems with multiplicative noise, Doklady Mathematics 93(2): 1–3.
  • [29] Zhou, K., Doyle, J.C. and Glover, K. (1996). Robust and Optimal Control, Prentice Hall, Englewood Cliffs, NJ.
  • [30] Zhou, K., Glover, K., Bodenheimer, B. and Doyle, J. (1994). Mixed H2 and H∞ performance objectives. I: Robust performance analysis, IEEE Transactions on Automatic Control 39(8): 1564–1574.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-81880a45-9f4d-4cff-b04d-40782f667b4a
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