Performing Aggressive Maneuvers using Iterative Learning Control
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Date
2009
Publication Type
Conference Paper
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yes
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Abstract
This paper presents an algorithm to iteratively drive a system quickly from one state to another. A simple model which captures the essential features of the system is used to compute the reference trajectory as the solution of an optimal control problem. Based on a lifted domain description of that same model an iterative learning controller is synthesized by solving a linear least-squares problem. The non-causality of the approach makes it possible to anticipate recurring disturbances. Computational requirements are modest, allowing controller update in real-time. The experience gained from successful maneuvers can be used to significantly reduce transients when performing similar motions. The algorithm is successfully applied to a real quadrotor unmanned aerial vehicle. The results are presented and discussed.
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published
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Book title
2009 IEEE International Conference on Robotics and Automation
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Volume
Pages / Article No.
1731 - 1736
Publisher
IEEE
Event
IEEE International Conference on Robotics and Automation (ICRA 2009)