EECI 2012: Computer Session: TuLiP: Difference between revisions

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==  Additional Information ==
==  Additional Information ==
* <p>[http://sourceforge.net/apps/mediawiki/tulip-control/index.php?title=Main_Page TuLiP on SourceForge] </p>
* <p>[http://sourceforge.net/apps/mediawiki/tulip-control/index.php?title=Main_Page TuLiP on SourceForge] </p>
* <p>[https://www.cds.caltech.edu/subversion/nok/rhtlp/trunk/doc/build/html/index.html TuLiP Documentation] For guest access, use ''anonymous'' as username with no password </p>
* <p>[http://tulip-control.sourceforge.net/doc/ TuLiP Documentation] and [http://tulip-control.sourceforge.net/doc/install.html Installation instructions] </p>
* <p>[http://jtlv.ysaar.net/ JTLV Project Home Site] JTLV provides the framework for the underlying digital design synthesis routine used in TuLiP. </p>
* <p>[http://jtlv.ysaar.net/ JTLV Project Home Site] JTLV provides the framework for the underlying digital design synthesis routine used in TuLiP. </p>

Revision as of 03:40, 22 April 2012

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This lecture provides an overview of TuLiP, a Python-based software toolbox for the synthesis of embedded control software that is provably correct with respect to a GR[1] specifications. TuLiP combines routines for (1) finite state abstraction of control systems, (2) digital design synthesis from GR[1] specifications, and (3) receding horizon planning. The underlying digital design synthesis routine treats the environment as adversary; hence, the resulting controller is guaranteed to be correct for any admissible environment profile. TuLiP applies the receding horizon framework, allowing the synthesis problem to be broken into a set of smaller problems, and consequently alleviating the computational complexity of the synthesis procedure, while preserving the correctness guarantee.

A brief overview of TuLiP will be followed by hands-on exercises using the toolbox.


Lecture Materials

Further Reading

  • TuLiP: A Software Toolbox for Receding Horizon Temporal Logic Planning, T. Wongpiromsarn, U. Topcu, N. Ozay, H. Xu and R. M. Murray, Hybrid Systems: Computation and Control, 2011.

Additional Information