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Reliable Control for Stochastic Systems with Low Sensitivity

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Linear-Quadratic Controls in Risk-Averse Decision Making

Part of the book series: SpringerBriefs in Optimization ((BRIEFSOPTI))

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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.

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References

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Authors and Affiliations

  1. The Air Force Research Laboratory, Space Vehicles Directorate, 3550 Aberdeen Ave. S.E., Kirtland Air Force Base, New Mexico, USA

    Khanh D. Pham

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  1. Khanh D. Pham
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© 2013 Khanh D. Pham

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Pham, K.D. (2013). Reliable Control for Stochastic Systems with Low Sensitivity. In: Linear-Quadratic Controls in Risk-Averse Decision Making. SpringerBriefs in Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5079-5_7

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