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Title: Geometric Attitude Control via Contraction on Manifolds with Automatic Gain Selection
In this paper we propose a new analysis of a simple geometric attitude controller, showing that it is locally exponentially stable and almost globally asymptotically stable; the exponential convergence region is much larger than existing non-hybrid geometric controllers (and covers almost the entire rotation space). The controller's stability is proved using contraction analysis combined with optimization. The key in this combination is that the contraction metric is a linear matrix inequality with a special structure stemming from the configuration manifold SO(3). As an additional contribution, we propose a general framework to automatically select controller gains by optimizing bounds on the system's convergence rate; while this principle is quite general, its application is particularly straightforward with our contraction-based analysis. We demonstrate our results through simulations.  more » « less
Award ID(s):
1728277
PAR ID:
10179919
Author(s) / Creator(s):
;
Date Published:
Journal Name:
IEEE Conference on Decision and Control (CDC)
Page Range / eLocation ID:
6138 to 6145
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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