Risk-averse control of linear stochastic systems with low sensitivity: A state-feedback paradigm

Author

Pham, Khanh D.

Author_Institution

Space Vehicles Directorate, Air Force Res. Lab., Kirtland AFB, NM, USA

fYear

2012

fDate

3-6 July 2012

Firstpage

66

Lastpage

72

Abstract

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

linear systems; matrix algebra; nonlinear equations; optimal control; state feedback; statistics; stochastic systems; linear feedback; linear stochastic systems; low sensitivity; mathematical statistics; nonlinear matrix equations; optimal full state-feedback control law; performance uncertainty; quadratic criterion; risk-averse control; sensitivity variables; Differential equations; Equations; Hafnium; Measurement uncertainty; Optimal control; Performance analysis; Sensitivity;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation (MED), 2012 20th Mediterranean Conference on

Conference_Location

Barcelona

Print_ISBN

978-1-4673-2530-1

Electronic_ISBN

978-1-4673-2529-5

Type

conf

DOI

10.1109/MED.2012.6265616

Filename

6265616