A Convex Data-Driven Approach for Nonlinear Control Synthesis
We consider a class of nonlinear control synthesis problems where the underlying mathematical models are not explicitly known. We propose a data-driven approach to stabilize the systems when only sample trajectories of the dynamics are accessible. Our method is built on the density-function-based st...
Main Authors: | Hyungjin Choi, Umesh Vaidya, Yongxin Chen |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-10-01
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Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/9/19/2445 |
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