NCS: Real-Time Trajectory Generation: Difference between revisions

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{{cds270-2 header}} <!-- Generates the header, including table of contents and link back to main page -->
{{cds270-2 header}} <!-- Generates the header, including table of contents and link back to main page -->


<!-- Enter a 1 paragraph description of the contents of the lectureMake sure to include any key concepts, so that the wiki search feature will pick them up -->
In this lecture we provide an overview of real-time trajectory generation for nonlinear control systems.  Using the concept of differential flatness, we show how to convert the trajectory generation problem from one in optimal control to one of optimizationEfficient numerical methods can then be used to find trajectories that satify the system dynamics and constraints, as well as minimizing a cost functionWe concentrate on methods for real-time trajectory generation, and in particular the [[NTG]] software package.
This is the template for CDS 270 lecturesIf you edit this page, you will see comments describing what goes in each section.  '''Do not edit this template.''' See [[CDS 270: Information for Lecturers]] for more information on how to create a wiki page corresponding to a lecture.


== Lecture Materials ==
== Lecture Materials ==
<!-- Include links to materials that you used in your lecture.  At a minimum, this should include a link to your lecture presentation.  You might also include links to MATLAB scripts or other source code that students would find useful -->
* [[Media:L3-1_ntg.pdf|Lecture: Nonlinear Trajectory Generation]]
<!-- Sample lecture link: * [[Media:L1-1_Intro.pdf|Lecture: Networked Control Systems: Course Overview]] -->


== Reading ==
== Reading ==

Revision as of 23:21, 7 April 2006

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In this lecture we provide an overview of real-time trajectory generation for nonlinear control systems. Using the concept of differential flatness, we show how to convert the trajectory generation problem from one in optimal control to one of optimization. Efficient numerical methods can then be used to find trajectories that satify the system dynamics and constraints, as well as minimizing a cost function. We concentrate on methods for real-time trajectory generation, and in particular the NTG software package.

Lecture Materials

Reading

Additional Resources