Title :
Risk-averse control of linear stochastic systems with low sensitivity: A state-feedback paradigm
Author_Institution :
Space Vehicles Directorate, Air Force Res. Lab., Kirtland AFB, NM, USA
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;
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
DOI :
10.1109/MED.2012.6265616
