Title :
Optimal feedback control strategies for state-space systems with stochastic parameters
Author :
Lee, Jay H. ; Cooley, Brian L.
Author_Institution :
Dept. of Chem. Eng., Auburn Univ., AL, USA
fDate :
10/1/1998 12:00:00 AM
Abstract :
Two different optimal feedback laws are derived for state-space systems parametrized through an independent identically distributed vector sequence. Both feedback laws are obtained by minimizing the expectation of a multistep quadratic loss function at each time step. They differ on the assumptions made about the future inputs. The properties and implementability of the feedback laws are discussed for the infinite horizon case
Keywords :
closed loop systems; dynamic programming; feedback; optimal control; predictive control; state-space methods; closed loop systems; distributed vector sequence; dynamic programming; feedback; infinite horizon; model predictive control; multistep quadratic loss function; optimal control; optimisation; parameter uncertainty; state-space systems; Adaptive control; Covariance matrix; Feedback control; Infinite horizon; Optimal control; Predictive control; Predictive models; State feedback; Stochastic systems; Uncertain systems;
Journal_Title :
Automatic Control, IEEE Transactions on
