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A Neural Approximation to Continuous Time Reachability Computations

Author(s):

K. N. Niarchos, J. Lygeros
Conference/Journal:

IEEE Conference on Decision and Control, San Diego, USA.
Abstract:

A method for approximating viability computations using neural networks is developed, with the aim of combating the “curse of dimensionality”. The viability problem is first formulated in an optimal control setting. Our algorithm extracts random initial conditions and then uses randomization to explore the space of bang-bang controls in an attempt to find viable trajectories starting at the given initial condition. The cost for the best among these randomly selected controls is then used to train the neural network. We demonstrate our approach on 2- and 3-dimensional examples in aerodynamic envelope protection.

Year:

2006
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { NiaLyg:2006:IFA_2571,
    author={K. N. Niarchos and J. Lygeros},
    title={{A Neural Approximation to Continuous Time Reachability
	  Computations}},
    booktitle={IEEE Conference on Decision and Control},
    pages={},
    year={2006},
    address={San Diego, USA.},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=2571}
}
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