Stochastic receding horizon control with output feedback and bounded control inputs
Abstract
We provide a solution to the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and imperfect state measurements. For a suitable choice of control policies, we show that the finite-horizon optimization problem to be solved on-line is convex and successively feasible. Due to the inherent nonlinearity of the feedback loop, a slight extension of the Kalman filter is exploited to estimate the state optimally in mean-square sense. We show that the receding horizon implementation of the resulting control policies renders the state of the overall system mean-square bounded under mild assumptions. Finally, we discuss how some of the quantities required by the finite-horizon optimization problem can be computed off-line, reducing the on-line computation, and present some numerical examples.
Cite
@article{arxiv.1001.3015,
title = {Stochastic receding horizon control with output feedback and bounded control inputs},
author = {Peter Hokayem and Eugenio Cinquemani and Debasish Chatterjee and Federico Ramponi and John Lygeros},
journal= {arXiv preprint arXiv:1001.3015},
year = {2010}
}
Comments
25 pages, 4 figures