Scenario-Based Set Invariance Verification for Black-Box Nonlinear Systems
(2020) IEEE Control Systems Letters — Vol. 5, n° 1, p. 193-198 (2021)
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- Abstract
- We consider the problem of set invariance verification in black-box nonlinear systems without analytic dynamical models. A data-driven set invariance verification approach relying on the observation of trajectories is proposed to determine almost-invariant sets, which are invariant almost everywhere except possibly in a small subset. With these observations, scenario optimization problems are formulated. We show that probabilistic invariance guarantees on the almost-invariant sets can be established. To get explicit expressions of such sets, a set identification procedure is designed by the use of a polynomial classifier. The practical performance of the proposed data-driven framework is illustrated by numerical examples.
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Wang, Z., & Jungers, R. (2020). Scenario-Based Set Invariance Verification for Black-Box Nonlinear Systems. IEEE Control Systems Letters, 5(1), 193-198. https://doi.org/10.1109/lcsys.2020.3001882 (Original work published 2021)