Abstract
This research stems from a control problem for a suspension device. For a general class of switching stochastic mechanical systems (including closed-loop control ones), we establish the following: (1) existence and uniqueness of a weak solution and its strong Markov property, (2) mixing property in the form of the local Markov–Dobrushin condition, and (3) exponentially fast convergence to the unique stationary distribution. These results are proved for discontinuous coefficients under nondegenerate disturbances in the force field; for (3) a stability condition is additionally imposed. Linear growth of coefficients is allowed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abourashchi, N., Veretennikov, A. Yu.: On stochastic averaging and mixing. Theory of Stoch. Processes. 16(1), 111–130 (2010)
Anulova, S., Pragarauskas, H.: Weak Markov solutions of stochastic equations. Lith. Math. J. 17(3), 141–155 (1978)
Anulova, S., Veretennikov, A.: On ergodic properties of degenerate hybrid stochastic control systems. In: 49th IEEE Conference on Decision and Control (CDC), 2010, Issue Date: 15–17 Dec. 2010, pp. 2292–2297. Location: Atlanta, GA (2010) doi:10.1109/CDC.2010.5717412
Arapostathis, A., Borkar, V.S., Ghosh, M.K.: Ergodic control of diffusion processes. Encyclopedia of Mathematics and its Applications 143. xvi, 323 p. Cambridge University Press, Cambridge. (2012)
Athreya, K., Kliemann, W., Koch, G.: On sequential construction of solutions of stochastic differential equations with jump terms. Syst. Control Lett. 10, 141–146 (1988)
Bujorianu, M., Lygeros, J.: Toward a general theory of stochastic hybrid systems. In: Blom, H., Lygeros, J. (eds.) Stochastic Hybrid Systems, pp. 3–30. Springer, Berlin (2006) http://www.springerlink.com/index/n62r24355788p6h7.pdf
Buyukkoroglu, T., Esen, O., Dzhafarov, V.: Common lyapunov functions for some special classes of stable systems. IEEE Trans. Automat Contr. 56, 1963–1967 (2011)
Campillo, F.: Optimal ergodic control for a class of nonlinear stochastic systems—Application to semi-active vehicle suspensions. In: Proceedings of the 28th IEEE Conference on Decision Control, pp. 1190–1195. Tampa (1989)
Campillo, F., Pardoux, E.: Numerical methods in ergodic optimal stochastic control and application. In: Karatzas, I., Ocone, D. (eds.) Applied Stochastic Analysis, pp. 59–73. Springer, Berlin (1992) http://www.springerlink.com/index/y13p561655383ht7.pdf
Davis, M.H.A.: Piecewise-Deterministic Markov Processes: A General class of non-diffusion stochastic models. J. Royal Stat. Soc. Ser. B (Methodological) 46(3), 353–388 (1984)
Deng, F., Luo, Q., Mao, X., Pang, S.: Noise suppresses or expresses exponential growth. Syst. Control Lett. 57(3), 262–270 (2008)
Guglielmino, E., Sireteanu, T., Stammers, C., Ghita, G., Giuclea, M.: Semi-active Suspension Control: Improved Vehicle Ride and Road Friendliness. Springer, Berlin (2008)
Hu, G., Liu, M., Mao, X., Song, M.: Noise expresses exponential growth under regime switching Systems. Syst. Control Lett. 58(9), 691–699 (2009)
Ikeda, N., Watanabe, S.: Stochastic Differential Equations and Diffusion Processes. 2nd edn. North-Holland Mathematical Library, 24. xvi, 555 p. Amsterdam etc.: North-Holland; Tokyo: Kodansha Ltd. (1989)
Khasminskii, R., Zhu, C., Yin, G.: Stability of regime-switching diffusions. Stoch. Processes Appl. 117(8), 1037–1051 (2007)
Krylov, N.V.: On the selection of a Markov process from a system of processes and the construction of quasi-diffusion processes. Math. USSR, Izv. 7, 691–709 (1973)
Nummelin, E.: General irreducible Markov chains and non-negative operators. Cambridge Tracts in Mathematics, 83. XI, 156 p. Cambridge etc.: Cambridge University Press. (1984)
Shur, M.: Ergodic theorems for Markov processes. In: Prohorov, Ju.V.(ed.) Probability and Mathematical Statistics: Encyclopedia, pp. 825–827. Moscow, The Big Russian Encyclopedia, 911 p. (1999) ISBN 5-85270-265-X
Veretennikov, A.: On weak solution of an SDE. In: 10th Vilnius conference on Probability Theory and Mathematical Statistics, 28.06-02.07.2010, Vilnius, Lithuania, Abstracts of Communications, vol. 287, TEV Publishers, Vilnius (2010)
Veretennikov, A. Yu.: Bounds for the mixing rate in the theory of stochastic equations. Theory Probab. Appl. 32, 273–281 (1987)
Veretennikov, A. Yu.: On Polynomial mixing and convergence rate for stochastic difference and differential equations. Theory Probab. Appl. 44(2), 361–374 (2000)
Veretennikov, A. Yu., Zverkina, G.A.: Simple proof of Dynkin’s formula for single–server systems and polynomial convergence rates. arXiv:1306.2359v1 [math.PR]
Wu, L.: Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems. Stoch. Processes Appl. 91(2), 205–238 (2001)
Yuan, C., Mao, X.: Asymptotic stability in distribution of stochastic differential equations with Markovian switching. Stoch. Processes Appl. 103(2), 277–291 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Anulova, S.V., Veretennikov, A.Y. (2014). Exponential Convergence of Degenerate Hybrid Stochastic Systems with Full Dependence. In: Korolyuk, V., Limnios, N., Mishura, Y., Sakhno, L., Shevchenko, G. (eds) Modern Stochastics and Applications. Springer Optimization and Its Applications, vol 90. Springer, Cham. https://doi.org/10.1007/978-3-319-03512-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-03512-3_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03511-6
Online ISBN: 978-3-319-03512-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)