We consider systems that are governed by linear time-discrete dynamics with an initial condition and a terminal condition for the expected values. We study optimal control problems where in the objective function a term of tracking type for the expected values and a control cost appear. In addition, the feasible states have to satisfy a conservative probabilistic constraint that requires that the probability that the trajectories remain in a given set F is greater than or equal to a given lower bound. An application are optimal control problems related to storage management systems with uncertain in- and output. We give sufficient conditions that imply that the optimal expected trajectories remain close to a certain state that can be characterized as the solution of an optimal control problem without prescribed initial- and terminal condition. In this way we contribute to the study of the turnpike phenomenon that is well-known in mathematical economics and make a step towards the extension of the turnpike theory to problems with probabilistic constraints.

Contact details are reproduced from the original publication and may be historical.

Martin Gugat

Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

martin.gugat@fau.de
  1. D. Adelhütte, D. Aßmann, T. Gonzlez Grandon, M. Gugat, H. Heitsch, F. Liers, R. Henrion, S. Nitsche, R. Schultz, M. Stingl, D. Wintergerst: Joint model of probabilistic/robust (probust) constraints with application to gas network optimization, Vietnam J. Math. 49 (2021) 1097–1130.https://doi.org/10.1007/s10013-020-00434-yGoogle Scholar
  2. J. Andersson, S. Grönkvist: Large-scale storage of hydrogen, Int. J. Hydrogen Energy 44/2 (2019) 11901–11919.https://doi.org/10.1016/j.ijhydene.2019.03.063Google Scholar
  3. T. Damm, L. Grüne, M. Stieler, K. Worthmann: An exponential turnpike theorem for dissipative discrete time optimal control problems, SIAM J. Control Optim. 52/3 (2014) 1935–1957.https://doi.org/10.1137/120888934Google Scholar
  4. R. Dorfman, P. A. Samuelson, R. M. Solow: Linear Programming and Economic Analysis, McGraw-Hill, New York (1958).Google Scholar
  5. M. H. Farshbaf-Shaker, M. Gugat, H. Heitsch, R. Henrion: Optimal Neumann boundary control of a vibrating string with uncertain initial data and probabilistic terminal constraints, SIAM J. Control Optim. 58/4 (2020) 2288–2311.https://doi.org/10.1137/19M1269944Google Scholar
  6. M. H. Farshbaf-Shaker, R. Henrion, D. Hömberg: Properties of chance constraints in infinite dimensions with an application to PDE constrained optimization, Set-Valued Var. Analysis 26 (2018) 821–841.https://doi.org/10.1007/s11228-017-0452-5Google Scholar
  7. T. Faulwasser, M. Korda, C. N. Jones, D. Bonvin: On turnpike and dissipativity properties of continuous-time optimal control problems, Automatica 81 (2017) 297–304.https://doi.org/10.1016/j.automatica.2017.03.012Google Scholar
  8. A. Geletu, A. Hoffmann, P. Schmidt, P. Li: Chance constrained optimization of elliptic PDE systems, ESAIM, Control Optim. Calc. Var. 26 (2020), 70 p.https://doi.org/10.1051/cocv/2019077Google Scholar
  9. T. González Grandón, H. Heitsch, R. Henrion: A joint model of probabilistic/robust constraints for gas transport management in stationary networks, Comput. Manage. Sci. 14/3 (2017) 443–460.https://doi.org/10.1007/s10287-017-0284-7Google Scholar
  10. L. Grüne, R. Guglielmi: Turnpike properties and strict dissipativity for discrete time linear quadratic optimal control problems, SIAM J. Control Optim. 56/2 (2018) 1282–1302.https://doi.org/10.1137/17M112350XGoogle Scholar
  11. L. Grüne, M. Schaller, A. Schiela: Exponential sensitivity and turnpike analysis for linear quadratic optimal control of general evolution equations, J. Diff. Equations 268/12 (2020) 7311–7341.https://doi.org/10.1016/j.jde.2019.11.064Google Scholar
  12. L. Grüne, M. Schaller, A. Schiela: Abstract nonlinear sensitivity and turnpike analysis and an application to semilinear parabolic PDEs, ESAIM, Control Optim. Calc. Var. 27 (2021), art. no. 56, 28 p.https://doi.org/10.1051/cocv/2021030Google Scholar
  13. M. Gugat: On the turnpike property with interior decay for optimal control problems, Math. Control Signals Systems 33 (2021) 237–258.https://doi.org/10.1007/s00498-021-00280-4Google Scholar
  14. H. A. Loiaciga: On the use of chance constraints in reservoir design and operation modeling, Water Resources Manage. 24 (1988) 1969–1975.https://doi.org/10.1029/WR024i011p01969Google Scholar
  15. J. Martínez-Frutos, F. Periago Esparza: Optimal Control of PDEs under Uncertainty, Springer, Berlin (2018).https://doi.org/10.1007/978-3-319-98210-6Google Scholar
  16. A. Prékopa: Stochastic Programming, Kluwer Academic, Dordrecht (1995).https://doi.org/10.1007/978-94-017-3087-7Google Scholar
  17. A. Ruszczyński: Nonlinear Optimization, Princeton University Press, Princeton (2006).https://doi.org/10.1515/9781400841059Google Scholar
  18. E. Trélat, C. Zhang, E. Zuazua: Steady-state and periodic exponential turnpike property for optimal control problems in Hilbert spaces, SIAM J. Control Optim. 56/2 (2018) 1222–1252.https://doi.org/10.1137/16M1097638Google Scholar
  19. W. van Ackooij, R. Zorgati, R. Henrion, A. Möller: Joint chance constrained programming for hydro reservoir management, Optim. Engineering 15 (2014) 509–531.https://doi.org/10.1007/s11081-013-9236-4Google Scholar
  20. A. J. Zaslavski: Turnpike Properties in the Calculus of Variations and Optimal Control, Nonconvex Optimization and its Applications 80, Springer, New York (2006).Google Scholar
  21. A. J. Zaslavski: Turnpike Phenomenon and Infinite Horizon Optimal Control, Springer Optimization and its Applications 99, Springer, Cham (2014).https://doi.org/10.1007/978-3-319-08828-0Google Scholar

M. Gugat, H. Heitsch, R. Henrion. “A Turnpike Property for Optimal Control Problems with Dynamic Probabilistic Constraints.” Journal of Convex Analysis 30 (2023), No. 3, 1025–1052. https://doi.org/10.68381/jca30047