Linear Matrix Inequality Approaches to Koopman Operator Approximation

Steven Dahdah; James Richard Forbes

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arXiv · 2102.03613

Linear Matrix Inequality Approaches to Koopman Operator Approximation

Steven Dahdah·James Richard Forbes

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Abstract

The regression problem associated with finding a matrix approximation of the Koopman operator from data is considered. The regression problem is formulated as a convex optimization problem subject to linear matrix inequality (LMI) constraints. Doing so allows for additional LMI constraints to be incorporated into the regression problem. In particular, asymptotic stability constraints, regularization using matrix norms, and even regularization using system norms can be easily incorporated into the regression problem.

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Steven Dahdah, James Richard Forbes. 2021-02-06. Linear Matrix Inequality Approaches to Koopman Operator Approximation. https://arxiv.org/abs/2102.03613

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