Difference between revisions of "EECI 2013: Computer Session: TuLiP"

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==  Lecture Materials ==
 
==  Lecture Materials ==
* Lecture slides: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/C2_tulip-17May12.pdf TuLiP] (Exercises are at the end of the slides.)
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* Lecture slides: [http://www.cds.caltech.edu/~utopcu/eeci13/C2_TuLiP-2013.pdf TuLiP] (Exercises are at the end of the slides.)
 
* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
 
* MATLAB plotting: [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotRobotSim.m plotRobotSim.m], [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/plotCarSim.m plotCarSim.m]
 
* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):  
 
* [http://www.cds.caltech.edu/~murray/courses/eeci-sp12/tulip_examples.zip Example TuLiP files] (zip file):  

Revision as of 19:59, 20 March 2013

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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

Additional Information