Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems of Markovian regime switching system
ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 69

This paper investigates the stochastic linear quadratic (LQ, for short) optimal control problem of Markovian regime switching system. The representation of the cost functional for the stochastic LQ optimal control problem of Markovian regime switching system is derived by the technique of Itô’s formula with jumps. For the stochastic LQ optimal control problem of Markovian regime switching system, we establish the equivalence between the open-loop (closed-loop, resp.) solvability and the existence of an adapted solution to the corresponding forward-backward stochastic differential equation with constraint. (i.e., the existence of a regular solution to Riccati equations). Also, we analyze the interrelationship between the strongly regular solvability of Riccati equations and the uniform convexity of the cost functional. Finally, we present an example which is open-loop solvable but not closed-loop solvable.

Reçu le :
Accepté le :
Première publication :
Publié le :
DOI : 10.1051/cocv/2021066
Classification : 49N10, 93E20
Keywords: Linear quadratic optimal control, markovian regime switching, Riccati equations, open-loop solvability, closed-loop solvability
@article{COCV_2021__27_1_A71_0,
     author = {Zhang, Xin and Li, Xun and Xiong, Jie},
     title = {Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems of {Markovian} regime switching system},
     journal = {ESAIM: Control, Optimisation and Calculus of Variations},
     year = {2021},
     publisher = {EDP-Sciences},
     volume = {27},
     doi = {10.1051/cocv/2021066},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/cocv/2021066/}
}
TY  - JOUR
AU  - Zhang, Xin
AU  - Li, Xun
AU  - Xiong, Jie
TI  - Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems of Markovian regime switching system
JO  - ESAIM: Control, Optimisation and Calculus of Variations
PY  - 2021
VL  - 27
PB  - EDP-Sciences
UR  - https://www.numdam.org/articles/10.1051/cocv/2021066/
DO  - 10.1051/cocv/2021066
LA  - en
ID  - COCV_2021__27_1_A71_0
ER  - 
%0 Journal Article
%A Zhang, Xin
%A Li, Xun
%A Xiong, Jie
%T Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems of Markovian regime switching system
%J ESAIM: Control, Optimisation and Calculus of Variations
%D 2021
%V 27
%I EDP-Sciences
%U https://www.numdam.org/articles/10.1051/cocv/2021066/
%R 10.1051/cocv/2021066
%G en
%F COCV_2021__27_1_A71_0
Zhang, Xin; Li, Xun; Xiong, Jie. Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems of Markovian regime switching system. ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 69. doi: 10.1051/cocv/2021066

[1] J.-M. Bismut, Linear quadratic optimal stochastic control with random coefficients. SIAM J. Control Optim. 14 (1976) 419–444.

[2] S. Chen, X. Li and X. Zhou, Stochastic linear quadratic regulators with indefinite control weight costs. SIAM J. Control Optim. 36 (1998) 1685–1702.

[3] S. Chen and J. Yong, Stochastic linear quadratic optimal control problems. Appl. Math. Optim. 43 (2001) 21–45.

[4] Y. Hu and B. Oksendal, Partial information linear quadratic control for jump diffusions. SIAM J. Control Optim. 47 (2008) 1744–1761.

[5] J. Huang and Z. Yu, Solvability of indefinite stochastic Riccati equations and linear quadratic optimal control problems. Syst. Control Lett. 68 (2014) 68–75.

[6] Y. Ji and H. Chizeck, Jump linear quadratic Gaussian control in continuous time. IEEE Trans. Autom. Control. 37 (1992) 1884–1892.

[7] Y. Ji and H. Chizeck, Controllability, stabilizability, and continuous-time Markovian jump linear quadratic control. IEEE Trans. Autom. Control. 35 (1990) 777–788.

[8] M. Kohlmann and S. Tang, New developments in backward stochastic riccati equations and their applications, in Mathematical Finance, edited by M. Kohlmann, S. Tang. Birkhäuser, Basel (2001) 194–214.

[9] M. Kohlmann and S. Tang, Global adapted solution of one-dimensional backward stochastic riccati equations, with application to the mean–variance hedging. Stoch. Process. Appl. 97 (2002) 255–288.

[10] M. Kohlmann and S. Tang, Minimization of risk and linear quadratic optimal control theory. SIAM J. Control Optim. 42 (2003) 1118–1142.

[11] M. Kohlmann and S. Tang, Multidimensional backward stochastic Riccati equations and applications. SIAM J. Control Optim. 41 (2003) 1696–1721.

[12] H. Kushner, Optimal stochastic control. IRE Trans. Autom. Control. 7 (1962) 120–122.

[13] N. Li, Z. Wu and Z. Yu, Indefinite stochastic linear-quadratic optimal control problems with random jumps and related stochastic Riccati equations. Sci. China Math. 61 (2018) 563–576.

[14] X. Li and X. Zhou, Indefinite stochastic LQ controls with Markovian jumps in a finite time horizon. Commun. Inf. Syst. 2 (2002) 265–282.

[15] X. Li, X. Zhou and M. Rami, Indefinite stochastic LQ control with jumps, in Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228). IEEE (2001).

[16] X. Li, X. Zhou and M. A. Rami, Indefinite stochastic linear quadratic control with Markovian jumps in infinite time horizon. J. Global Optim. 27 (2003) 149–175.

[17] Y. Liu, G. Yin and X. Y. Zhou, Near-optimal controls of random-switching LQ problems with indefinite control weight costs. Automatica. 41 (2005) 1063–1070.

[18] Q. Lv, T. Wang and X. Zhang, Characterization of optimal feedback for stochastic linear quadratic control problems. Probab. Uncert. Quant. Risk. 2 (2017) Article number: 11.

[19] H. Mei and J. Yong, Equilibrium strategies for time-inconsistent stochastic switching systems. ESAIM: COCV 25 (2019) Article number: 64.

[20] J. Sun, X. Li and J. Yong, Open-loop and closed-loop solvabilities for stochastic linear quadratic optimal control problems. SIAM J. Control Optim. 54 (2016) 2274–2308.

[21] J. Sun, J. Xiong and J. Yong, Stochastic linear-quadratic optimal control problems with random coefficients: closed-loop representation of open-loop optimal controls. Manuscript submitted for publication. (2018).

[22] J. Sun and J. Yong, Linear quadratic stochastic differential games: open-loop and closed-loop saddle points. SIAM J. Control Optim. 52 (2014) 4082–4121.

[23] J. Sun and J. Yong, Stochastic Linear-Quadratic Optimal Control Theory: Open-Loop and Closed-Loop Solutions. Springer International Publishing (2020).

[24] S. Tang, General linear quadratic optimal stochastic control problems with random coefficients: Linear stochastic Hamilton systems and backward stochastic Riccati equations. SIAM J. Control Optim. 42 (2003) 53–75.

[25] S. Tang, Dynamic programming for general linear quadratic optimal stochastic control with random coefficients. SIAM J. Control Optim. 53 (2015) 1082–1106.

[26] T. Wang, Necessary conditions in stochastic linear quadratic problems and their applications. J. Math. Anal. Appl. 469 (2019) 280–297.

[27] W. M. Wonham, On a matrix riccati equation of stochastic control. SIAM J. Control 6 (1968) 681–697.

[28] Z. Wu and X.-R. Wang, FBSDE with Poisson process and its application to linear quadratic stochastic optimal control problem with random jumps. Acta Autom. Sin. 29 (2003) 821–826.

[29] G. Yin, X. Zhou, Markowitz’s mean-variance portfolio selection with Regime switching: from discrete-time models to their continuous-time limits. IEEE Trans. Autom. Control. 49 (2004) 349–360.

[30] J. Yong and X. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations. Springer, New York (1999).

[31] Z. Yu, Infinite horizon jump-diffusion forward-backward stochastic differential equations and their application to backward linear-quadratic problems. ESAIM: COCV 23 (2017) 1331–1359.

[32] C. Zalinescu, On uniformly convex functions. J. Math. Anal. Appl. 95 (1983) 344–374.

[33] C. Zalinescu, Convex Analysis in General Vector Spaces. World Scientific (2002).

[34] Q. Zhang and G. Yin, On nearly optimal controls of hybrid LQG problems. IEEE Trans. Autom. Control. 44 (1999) 2271–2282.

[35] X. Zhang, R. J. Elliott and T. K. Siu, A stochastic maximum principle for a Markov regime-switching jump-diffusion model and its application to finance. SIAM J. Control Optim. 50 (2012) 964–990.

[36] X. Zhang, R. J. Elliott, T. K. Siu and J. Guo, Markovian regime-switching market completion using additional Markov jump assets. IMA J. Manag. Math. 23 (2011) 283–305.

[37] X. Zhang, T. K. Siu and Q. Meng, Portfolio selection in the enlarged Markovian regime-switching market. SIAM J. Control Optim. 48 (2010) 3368–3388.

[38] X. Zhang, Z. Sun and J. Xiong, A general stochastic maximum principle for a Markov regime switching jump-diffusion model of mean-field type. SIAM J. Control Optim. 56 (2018) 2563–2592.

[39] X. Zhou and G. Yin, Markowitz’s mean-variance portfolio selection with regime switching: a continuous-time model. SIAM J. Control Optim. 42 (2003) 1466–1482.

Cité par Sources :

The first author is supported by National Natural Science Foundation of China (grant no. 11771079) and Fundamental Research Funds for the Central Universities (grant no. 2242021R41082), the second author is supported by RGC Grants (grant nos. 15209614, 15213218 and 15215319) and partially from CAS AMSS-PolyU Joint Laboratory of Applied Mathematics, and the third author is supported by Southern University of Science and Technology Start up fund Y01286120 and National Natural Science Foundation of China (grant nos. 61873325, 11831010).