A linear-quadratic optimal control problem for mean-field stochastic differential equations in infinite horizon

Jianhui Huang; Xun Li; Jiongmin Yong

doi:10.3934/mcrf.2015.5.97

Article Contents

2015, Volume 5, Issue 1: 97-139. Doi: 10.3934/mcrf.2015.5.97

This issue Previous Article Optimal $L^2$-control problem in coefficients for a linear elliptic equation. I. Existence result Next Article State constrained patchy feedback stabilization

A linear-quadratic optimal control problem for mean-field stochastic differential equations in infinite horizon

1.
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
2.
Department of Mathematics, University of Central Florida, Orlando, FL 32816

Received: July 2013

Revised: November 2013

Published: March 2015

Abstract Related Papers Cited by

Abstract

A linear-quadratic (LQ, for short) optimal control problem is considered for mean-field stochastic differential equations with constant coefficients in an infinite horizon. The stabilizability of the control system is studied followed by the discussion of the well-posedness of the LQ problem. The optimal control can be expressed as a linear state feedback involving the state and its mean, through the solutions of two algebraic Riccati equations. The solvability of such kind of Riccati equations is investigated by means of semi-definite programming method.

Keywords:

Mean-field stochastic differential equation,
linear-quadratic optimal control,
MF-stabilizability,
Riccati equation.

Mathematics Subject Classification: Primary: 49N10, 49N35; Secondary: 93D15, 93E20, 90C22.

Citation:

Related Papers

Cited by

References

[1]	N. U. Ahmed and X. Ding, A semilinear McKean-Vlasov stochastic evolution equation in Hilbert space, Stoch. Proc. Appl., 60 (1995), 65-85.doi: 10.1016/0304-4149(95)00050-X.
[2]	N. U. Ahmed and X. Ding, Controlled McKean-Vlasov equations, Comm. Appl. Anal., 5 (2001), 183-206.
[3]	N. U. Ahmed, Nonlinear diffusion governed by McKean-Vlasov equation on Hilbert space and optimal control, SIAM J. Control Optim., 46 (2007), 356-378.doi: 10.1137/050645944.
[4]	M. Ait Rami and X. Y. Zhou, Linear matrix inequalities, Riccati equations, and indefinite stochastic linear quadratic controls, IEEE Transactions on Automatic Control, 45 (2000), 1131-1143.doi: 10.1109/9.863597.
[5]	A. Albert, Conditions for positive and nonnegative definiteness in terms of pseudo-inverses, SIAM J. Appl. Math., 17 (1969), 434-440.doi: 10.1137/0117041.
[6]	D. Andersson and B. Djehiche, A maximum principle for SDEs of mean-field type, Appl. Math. Optim., 63 (2011), 341-356.doi: 10.1007/s00245-010-9123-8.
[7]	A. Ben-Israel and T. N. E. Greville, Generalized Inverses, Springer-Verlag, 2003.
[8]	A. Bensoussan, G. Da Prato, M. C. Delfour and S. K. Mitter, Representation and Control of Infinite Dimensional Systems, 2nd edition, Systems & Control: Foundations & Applications. Birkhäuser Boston, Inc., Boston, 2007.doi: 10.1007/978-0-8176-4581-6.
[9]	V. S. Borkar and K. S. Kumar, McKean-Vlasov limit in portfolio optimization, Stoch. Anal. Appl., 28 (2010), 884-906.doi: 10.1080/07362994.2010.482836.
[10]	S. Boyd, L. El Ghaoul, E. Feron and V. Balakrishnan, Linear Matrix Inequality in Systems and Control Theory, SIAM, Philadelphia, 1994.doi: 10.1137/1.9781611970777.
[11]	R. Buckdahn, B. Djehiche and J. Li, A general maximum principle for SDEs of mean-field type, Applied Mathematics & Optimization, 64 (2011), 197-216.doi: 10.1007/s00245-011-9136-y.
[12]	R. Buckdahn, B. Djehiche, J. Li and S. Peng, Mean-field backward stochastic differential equations: A limit approach, Ann. Probab., 37 (2009), 1524-1565.doi: 10.1214/08-AOP442.
[13]	R. Buckdahn, J. Li and S. Peng, Mean-field backward stochastic differential equations and related partial differential equations, Stoch. Process. Appl., 119 (2009), 3133-3154.doi: 10.1016/j.spa.2009.05.002.
[14]	T. Chan, Dynamics of the McKean-Vlasov equation, Ann. Probab., 22 (1994), 431-441.doi: 10.1214/aop/1176988866.
[15]	T. Chiang, McKean-Vlasov equations with discontinuous coefficients, Soochow J. Math., 20 (1994), 507-526.
[16]	D. Crisan and J. Xiong, Approximate McKean-Vlasov representations for a class of SPDEs, Stochastics, 82 (2010), 53-68.doi: 10.1080/17442500902723575.
[17]	D. A. Dawson, Critical dynamics and fluctuations for a mean-field model of cooperative behavior, J. Statist. Phys., 31 (1983), 29-85.doi: 10.1007/BF01010922.
[18]	D. A. Dawson and J. Gärtner, Large deviations from the McKean-Vlasov limit for weakly interacting diffusions, Stochastics, 20 (1987), 247-308.doi: 10.1080/17442508708833446.
[19]	L. El Ghaoui and M. Ait Rami, Robust state-feedback stabilization of jump linear systems via LIMs, Int. J. Robust and Nonlinear Contr., 6 (1996), 1015-1022.doi: 10.1002/(SICI)1099-1239(199611)6:9/10<1015::AID-RNC266>3.0.CO;2-0.
[20]	J. Gärtner, On the Mckean-Vlasov limit for interacting diffusions, Math. Nachr., 137 (1988), 197-248.doi: 10.1002/mana.19881370116.
[21]	C. Graham, McKean-Vlasov Ito-Skorohod equations, and nonlinear diffusions with discrete jump sets, Stoch. Proc. Appl., 40 (1992), 69-82.doi: 10.1016/0304-4149(92)90138-G.
[22]	M. Grant and S. Boyd, Graph implementations for nonsmooth convex programs, Recent Advances in Learning and Control (a tribute to M. Vidyasagar), Lecture Notes in Control and Information Sciences, Springer, 371 (2008), 95-110.doi: 10.1007/978-1-84800-155-8_7.
[23]	M. Huang, R. P. Malhamé, and P. E. Caines, Large population stochastic dynamic games: Closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle, Comm. Inform. Systems, 6 (2006), 221-251.doi: 10.4310/CIS.2006.v6.n3.a5.
[24]	M. Kac, Foundations of kinetic theory, Proc. 3rd Berkeley Sympos. Math. Statist. Prob., 3 (1956), 171-197.
[25]	P. E. Kloeden and T. Lorenz, Stochastic differential equations with nonlocal sample dependence, Stoch. Anal. Appl., 28 (2010), 937-945.doi: 10.1080/07362994.2010.515194.
[26]	P. M. Kotelenez and T. G. Kurtz, Macroscopic limit for stochastic partial differential equations of McKean-Vlasov type, Prob. Theory Rel. Fields, 146 (2010), 189-222.doi: 10.1007/s00440-008-0188-0.
[27]	J. M. Lasry and P. L. Lions, Mean field games, Japan J. Math., 2 (2007), 229-260.doi: 10.1007/s11537-007-0657-8.
[28]	X. Li, X.Y. Zhou and M. Ait Rami, Indefinite stochastic linear quadratic control with Markovian jumps in infinite time horizon, Journal of Global Optimization, 27 (2003), 149-175.doi: 10.1023/A:1024887007165.
[29]	H. P. McKean, A class of Markov processes associated with nonlinear parabolic equations, Proc. Natl. Acad. Sci. USA, 56 (1966), 1907-1911.doi: 10.1073/pnas.56.6.1907.
[30]	T. Meyer-Brandis, B. /'Oksendal and X. Y. Zhou, A mean-field stochastic maximum principle via Malliavin calculus, Stochastics, 84 (2012), 643-666.doi: 10.1080/17442508.2011.651619.
[31]	J. Y. Park, P. Balasubramaniam and Y. H. Kang, Controllability of McKean-Vlasov stochastic integrodifferential evolution equation in Hilbert spaces, Numer. Funct. Anal. Optim., 29 (2008), 1328-1346.doi: 10.1080/01630560802580679.
[32]	R. Penrose, A generalized inverse of matrices, Proc. Cambridge Philos. Soc., 51 (1955), 406-413.doi: 10.1017/S0305004100030401.
[33]	M. Scheutzow, Uniqueness and non-uniqueness of solutions of Vlasov-McKean equations, J. Austral. Math. Soc., Ser. A, 43 (1987), 246-256.doi: 10.1017/S1446788700029384.
[34]	R. H Tutuncu, K. C. Toh, and M. J. Todd, Solving semidefinite-quadratic-linear programs using SDPT3, Mathematical Programming Ser. B, 95 (2003), 189-217.doi: 10.1007/s10107-002-0347-5.
[35]	L. Vandenerghe and S. Boyd, Semidefinite programming, SIAM Rev., 38 (1996), 49-95.doi: 10.1137/1038003.
[36]	A. Yu. Veretennikov, On ergodic measures for McKean-Vlasov stochastic equations, in Monte Carlo and quasi-Monte Carlo methods 2004, Springer, Berlin, 2006, 471-486.doi: 10.1007/3-540-31186-6_29.
[37]	J. Yong, Linear-quadratic optimal control problems for mean-field stochastic differential equations, SIAM J. Control Optim., 51 (2013), 2809-2838.doi: 10.1137/120892477.
[38]	J. Yong and X. Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations, Applications of Mathematics (New York), 43, Springer-Verlag, New York, 1999.doi: 10.1007/978-1-4612-1466-3.