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Title: Koopman-Inspired Implicit Backward Reachable Sets for Unknown Nonlinear Systems
Koopman liftings have been successfully used to learn high dimensional linear approximations for autonomous systems for prediction purposes, or for control systems for leveraging linear control techniques to control nonlinear dynamics. In this paper, we show how learned Koopman approximations can be used for state-feedback correct-by-construction control. To this end, we introduce the Koopman over-approximation, a (possibly hybrid) lifted representation that has a simulation-like relation with the underlying dynamics. Then, we prove how successive application of controlled predecessor operation in the lifted space leads to an implicit backward reachable set for the actual dynamics. Finally, we demonstrate the approach on two nonlinear control examples with unknown dynamics.  more » « less
Award ID(s):
1931982
NSF-PAR ID:
10481566
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IEEE Control Systems Letters
Date Published:
Journal Name:
IEEE Control Systems Letters
Volume:
7
ISSN:
2475-1456
Page Range / eLocation ID:
2245 to 2250
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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