N. Altmüller and L. Grüne, Distributed and boundary model predictive control for the heat equation, GAMM-Mitt, pp.131-145, 2012.

N. Altmüller and L. Grüne, A comparative stabiliy analysis of Neumann and Dirichlet boundary MPC for the heat equation, Proceedings of the 1st IFAC Workshop on Control of Systems Modeled by Partial Differential Equations ? CPDE 2013, pp.161-166, 2013.

M. Annunziato and A. Borz, Optimal control of probability density functions of stochastic processes*, Mathematical Modelling and Analysis, vol.15, issue.4, pp.393-407, 2010.
DOI : 10.3846/1392-6292.2010.15.393-407

M. Annunziato and A. Borz, A Fokker???Planck control framework for multidimensional stochastic processes, Journal of Computational and Applied Mathematics, vol.237, issue.1, pp.487-507, 2013.
DOI : 10.1016/j.cam.2012.06.019

A. Blaquiere, Controllability of a Fokker-Planck equation, the Schr??dinger system, and a related stochastic optimal control (revised version), Dynamics and Control, vol.41, issue.1, pp.235-253, 1992.
DOI : 10.1007/BF02169515

R. Brockett, New issues in the mathematics of control, Mathematics unlimited?2001 and beyond, pp.189-219, 2001.

S. Dubljevic and P. D. Christofides, Boundary predictive control of parabolic PDEs, 2006 American Control Conference, pp.49-56, 2006.
DOI : 10.1109/ACC.2006.1655329

S. Dubljevic, N. H. El-farra, P. Mhaskar, and P. D. Christofides, Predictive control of parabolic PDEs with state and control constraints, International Journal of Robust and Nonlinear Control, vol.50, issue.16, pp.749-772, 2006.
DOI : 10.1002/rnc.1097

W. H. Fleming and R. W. , Deterministic and Stochastic Optimal Control, 1975.
DOI : 10.1007/978-1-4612-6380-7

M. G. Forbes, M. Guay, and J. F. Forbes, Control design for first-order processes: shaping the probability density of the process state, Journal of Process Control, vol.14, issue.4, pp.399-410, 2004.
DOI : 10.1016/j.jprocont.2003.07.002

L. Grüne, NMPC without terminal constraints, Proceedings of the IFAC Conference on Nonlinear Model Predictive Control 2012 ? NMPC'12, pp.1-13, 2012.
DOI : 10.3182/20120823-5-NL-3013.00030

L. Grüne and J. Pannek, Nonlinear Model Predictive Control. Theory and Algorithms, 2011.

G. Jumarie, Tracking control of non-linear stochastic systems by using path cross-entropy and Fokker-Planck equation, International Journal of Systems Science, vol.23, issue.7, pp.1101-1114, 1992.
DOI : 10.1007/BF00935628

M. Karny, Towards fully probabilistic control design, Automatica, vol.32, issue.12, pp.1719-1722, 1996.
DOI : 10.1016/S0005-1098(96)80009-4

K. Ito and K. Kunisch, Receding horizon optimal control for infinite dimensional systems, ESAIM: Control, Optimisation and Calculus of Variations, vol.8, pp.741-760, 2002.
DOI : 10.1051/cocv:2002032

A. Porretta, On the planning problem for a class of Mean Field Games, Comptes Rendus Mathematique, vol.351, issue.11-12, pp.457-462, 2013.
DOI : 10.1016/j.crma.2013.07.004

J. B. Rawlings and D. Q. Mayne, Model Predictive Control: Theory and Design, 2009.

S. J. Qin and T. A. , A survey of industrial model predictive control technology, Control Engineering Practice, vol.11, issue.7, pp.733-764, 2003.
DOI : 10.1016/S0967-0661(02)00186-7

R. Risken, The Fokker-Planck Equation: Methods of Solution and Application, 2nd ed., Journal of Applied Mechanics, vol.58, issue.3, 1996.
DOI : 10.1115/1.2897281

H. Wang, Robust control of the output probability density functions for multivariable stochastic systems with guaranteed stability, IEEE Transactions on Automatic Control, vol.44, issue.11, pp.2103-2107, 1999.
DOI : 10.1109/9.802925