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Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

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  • Jiang Wu
  • Fucheng Liao
  • Masayoshi Tomizuka

Abstract

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

Suggested Citation

  • Jiang Wu & Fucheng Liao & Masayoshi Tomizuka, 2017. "Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(1), pages 129-137, January.
  • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:1:p:129-137
    DOI: 10.1080/00207721.2016.1160456
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    References listed on IDEAS

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    1. Anne Eyraud-Loisel, 2005. "Backward stochastic differential equations with enlarged filtration: Option hedging of an insider trader in a financial market with jumps," Post-Print hal-01298905, HAL.
    2. Eyraud-Loisel, Anne, 2005. "Backward stochastic differential equations with enlarged filtration: Option hedging of an insider trader in a financial market with jumps," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1745-1763, November.
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    Cited by:

    1. Li Li & Fucheng Liao, 2020. "Preview Control for MIMO Discrete-Time System with Parameter Uncertainty," Mathematics, MDPI, vol. 8(5), pages 1-20, May.

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