Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.

  

Stochastic receding horizon control with bounded control inputs: a vector space approach

Author(s):

D. Chatterjee, P. Hokayem, J. Lygeros
Conference/Journal:

vol. AUT09-05, Also available at http://arxiv.org/abs/0903.5444
Abstract:

We design receding horizon control strategies for stochastic discrete-time linear systems with additive (possibly) unbounded disturbances, while obeying hard bounds on the control inputs. We pose the problem of selecting an appropriate optimal controller on vector spaces of functions and show that the resulting optimization problem has a tractable convex solution. Under the assumption that the zero-input and zero-noise system is asymptotically stable, we show that the variance of the state is bounded when enforcing hard bounds on the control inputs, for any receding horizon implementation. Throughout the article we provide several examples that illustrate how quantities needed in the formulation of the resulting optimization problems can be calculated off-line, as well as comparative examples that illustrate the effectiveness of our control strategies.

Year:

2009
Type of Publication:

(04)Technical Report
Supervisor:

J. Lygeros

File Download:

Request a copy of this publication.
(Uses JavaScript)
% Autogenerated BibTeX entry
@TechReport { ChaHok:2009:IFA_3284,
    author={D. Chatterjee and P. Hokayem and J. Lygeros},
    title={{Stochastic receding horizon control with bounded control
	  inputs: a vector space approach}},
    institution={},
    year={2009},
    number={},
    address={},
    month=mar,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3284}
}
Permanent link