Excitation of control-affine systems and Koopman error bounds
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911737387679744 |
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| author | Schmitz, Philipp Bold, Lea Philipp, Friedrich M. Rosenfelder, Mario Eberhard, Peter Ebel, Henrik Worthmann, Karl |
| author_facet | Schmitz, Philipp Bold, Lea Philipp, Friedrich M. Rosenfelder, Mario Eberhard, Peter Ebel, Henrik Worthmann, Karl |
| contents | The Koopman operator and extended dynamic mode decomposition (EDMD) as a data-driven technique for its approximation have attracted considerable attention as a key tool for modeling, analysis, and control of complex dynamical systems. However, extensions towards control-affine systems resulting in bilinear surrogate models are prone to demanding data requirements rendering their applicability intricate. In this paper, we propose a framework for data-fitting of control-affine mappings to increase the robustness margin in the associated system identification problem and, thus, to provide reliable bilinear EDMD schemes. In particular, guidelines for input selection based on subspace angles are deduced such that a desired threshold with respect to the minimal singular value is ensured. Moreover, we derive necessary and sufficient conditions of optimality for maximizing the minimal singular value. Further, we demonstrate the usefulness of the proposed approach using bilinear EDMD with control for nonholonomic robots. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_03734 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Excitation of control-affine systems and Koopman error bounds Schmitz, Philipp Bold, Lea Philipp, Friedrich M. Rosenfelder, Mario Eberhard, Peter Ebel, Henrik Worthmann, Karl Systems and Control Dynamical Systems 93B30, 15A18, 93C10, 37M25 The Koopman operator and extended dynamic mode decomposition (EDMD) as a data-driven technique for its approximation have attracted considerable attention as a key tool for modeling, analysis, and control of complex dynamical systems. However, extensions towards control-affine systems resulting in bilinear surrogate models are prone to demanding data requirements rendering their applicability intricate. In this paper, we propose a framework for data-fitting of control-affine mappings to increase the robustness margin in the associated system identification problem and, thus, to provide reliable bilinear EDMD schemes. In particular, guidelines for input selection based on subspace angles are deduced such that a desired threshold with respect to the minimal singular value is ensured. Moreover, we derive necessary and sufficient conditions of optimality for maximizing the minimal singular value. Further, we demonstrate the usefulness of the proposed approach using bilinear EDMD with control for nonholonomic robots. |
| title | Excitation of control-affine systems and Koopman error bounds |
| topic | Systems and Control Dynamical Systems 93B30, 15A18, 93C10, 37M25 |
| url | https://arxiv.org/abs/2511.03734 |