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Reliable Control for Stochastic Systems with Low Sensitivity

  • Khanh D. Pham
Chapter
  • 922 Downloads
Part of the SpringerBriefs in Optimization book series (BRIEFSOPTI)

Abstract

In this chapter, the problem of controlling stochastic linear systems with quadratic criterion which includes sensitivity variables is investigated. It is proved that the optimal full state-feedback control law with risk aversion can be realized by the cascade of mathematical statistics of performance uncertainty and a linear feedback. A set of nonlinear matrix equations are obtained, which constitutes the necessary and sufficient conditions that must be satisfied for an optimal solution.

Keywords

Performance Uncertainty Constant Variance Parameter Performance-measure Statistics Stationary Optimal Control Performance Risk Aversion 
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.

References

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Copyright information

© Khanh D. Pham 2013

Authors and Affiliations

  • Khanh D. Pham
    • 1
  1. 1.The Air Force Research LaboratorySpace Vehicles DirectorateKirtland Air Force BaseUSA

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