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Optimal control for state-space models

  • M. H. A. Davis
  • R. B. Vinter
Part of the Monographs on Statistics and Applied Probability book series (MSAP)

Abstract

This chapter concerns optimal control problems for the state-space models discussed in Chapters 2 and 3. The state and observation processes x k and y k are given respectively by the equations
$${x_{k + 1}} = A(k){x_k} + B(k){u_k} + C(k){w_k}$$
(6.0.1)
$${y_k} = H(k){x_k} + G(k){w_k}$$
(6.0.2)
where w k is a white-noise sequence. We now wish to choose the control sequence u k so that the system behaves in some desirable way. We have to settle two questions at the outset, namely what sort of controls are to be allowed (or, are admissible) and what the control objective is.

Keywords

Kalman Filter Riccati Equation Average Cost Bellman Equation Algebraic Riccati Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© M. H. A. Davis and R. B. Vinter 1985

Authors and Affiliations

  • M. H. A. Davis
    • 1
  • R. B. Vinter
    • 1
  1. 1.Department of Electrical EngineeringImperial CollegeLondonUK

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