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Optimal control for both forward and backward discrete-time systems

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Listed:
  • Chen, Xin
  • Yuan, Yue
  • Yuan, Dongmei
  • Ge, Xiao

Abstract

Forward discrete-time systems use past information to update the current state, while backward discrete-time systems use future information to update the current state. This study focuses on optimal control problems within the context of forward and backward discrete-time systems. We begin by investigating a general optimal control problem for both forward and backward discrete-time systems. Leveraging the inherent properties of these systems and the Bellman optimality principle, we derive recursive equations as a means to solve such optimal control problems. Using these recursive equations, we obtain analytical expressions for both the optimal controls and optimal values of bang–bang and linear quadratic optimal control problems. Finally, we present a numerical example and an industrial wastewater treatment problem to illustrate and demonstrate our findings.

Suggested Citation

  • Chen, Xin & Yuan, Yue & Yuan, Dongmei & Ge, Xiao, 2024. "Optimal control for both forward and backward discrete-time systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 298-314.
  • Handle: RePEc:eee:matcom:v:221:y:2024:i:c:p:298-314
    DOI: 10.1016/j.matcom.2024.03.009
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    References listed on IDEAS

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    1. Jaddu, Hussein, 2002. "Spectral method for constrained linear–quadratic optimal control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 58(2), pages 159-169.
    2. Duffie, Darrell & Epstein, Larry G, 1992. "Stochastic Differential Utility," Econometrica, Econometric Society, vol. 60(2), pages 353-394, March.
    3. Giorgio Ferrari & Torben Koch, 2019. "On a strategic model of pollution control," Annals of Operations Research, Springer, vol. 275(2), pages 297-319, April.
    4. N. El Karoui & S. Peng & M. C. Quenez, 1997. "Backward Stochastic Differential Equations in Finance," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 1-71, January.
    5. Waichon Lio & Baoding Liu, 2021. "Initial value estimation of uncertain differential equations and zero-day of COVID-19 spread in China," Fuzzy Optimization and Decision Making, Springer, vol. 20(2), pages 177-188, June.
    6. Yadong Shu & Yuanguo Zhu, 2018. "Optimal control for multi-stage and continuous-time linear singular systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(7), pages 1419-1434, May.
    7. Chen, Xin & Song, Yifu & Shao, Yu & Wang, Jian & He, Liu & Chen, Yuefen, 2024. "Optimistic value-based optimal control problems with uncertain discrete-time noncausal systems," Applied Mathematics and Computation, Elsevier, vol. 460(C).
    8. Kok Lay Teo & Bin Li & Changjun Yu & Volker Rehbock, 2021. "Applied and Computational Optimal Control," Springer Optimization and Its Applications, Springer, number 978-3-030-69913-0, June.
    9. Alt, Walter & Schneider, Christopher & Seydenschwanz, Martin, 2016. "Regularization and implicit Euler discretization of linear-quadratic optimal control problems with bang-bang solutions," Applied Mathematics and Computation, Elsevier, vol. 287, pages 104-124.
    10. Duffie, Darrell & Epstein, Larry G, 1992. "Asset Pricing with Stochastic Differential Utility," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 411-436.
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