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Stochastic Receding Horizon Control with Output Feedback and Bounded Control Inputs

Author(s):

P. Hokayem, E. Cinquemani, D. Chatterjee, F. Ramponi, J. Lygeros
Conference/Journal:

IEEE Conference on Decision and Control, pp. 6095-6100
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.

Year:

2010
Type of Publication:

(01)Article
Supervisor:

J. Lygeros

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% Autogenerated BibTeX entry
@InProceedings { HokEtal:2010:IFA_3680,
    author={P. Hokayem and E. Cinquemani and D. Chatterjee and F. Ramponi and J.
	  Lygeros},
    title={{Stochastic Receding Horizon Control with Output Feedback
	  and Bounded Control Inputs}},
    booktitle={IEEE Conference on Decision and Control},
    pages={6095--6100},
    year={2010},
    address={},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3680}
}
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