Title :
Stochastic receding horizon control with output feedback and bounded control inputs
Author :
Hokayem, Peter ; Cinquemani, Eugenio ; Chatterjee, Debasish ; Ramponi, Federico ; Lygeros, John
Author_Institution :
Autom. Control Lab., ETH Zurich, Zürich, Switzerland
Abstract :
We study the problem of receding horizon control of stochastic discrete-time systems with bounded control inputs and incomplete state information. Given a suitable choice of causal control policies, we first present a slight extension of the Kalman filter to estimate the state optimally in mean-square sense. We then show how to augment the underlying optimization problem with a negative drift-like constraint, yielding a second-order cone program to be solved periodically online. Finally, we prove that the receding horizon implementation of the resulting control policies renders the state of the overall system mean-square bounded under mild assumptions.
Keywords :
Kalman filters; discrete time systems; feedback; mean square error methods; optimisation; stochastic systems; Kalman filter; bounded control inputs; mean-square sense; optimization problem; output feedback; state information; stochastic discrete-time systems; stochastic receding horizon control; Noise; Noise measurement; Optimization; Process control; Robustness; State feedback; Yttrium;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717990