Controller Design for Bilinear Neural Feedback Loops
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912403754582016 |
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| author | Shah, Dhruv Cortés, Jorge |
| author_facet | Shah, Dhruv Cortés, Jorge |
| contents | This paper considers a class of bilinear systems with a neural network in the loop. These arise naturally when employing machine learning techniques to approximate general, non-affine in the input, control systems. We propose a controller design framework that combines linear fractional representations and tools from linear parameter varying control to guarantee local exponential stability of a desired equilibrium. The controller is obtained from the solution of linear matrix inequalities, which can be solved offline, making the approach suitable for online applications. The proposed methodology offers tools for stability and robustness analysis of deep neural networks interconnected with dynamical systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_24106 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Controller Design for Bilinear Neural Feedback Loops Shah, Dhruv Cortés, Jorge Systems and Control This paper considers a class of bilinear systems with a neural network in the loop. These arise naturally when employing machine learning techniques to approximate general, non-affine in the input, control systems. We propose a controller design framework that combines linear fractional representations and tools from linear parameter varying control to guarantee local exponential stability of a desired equilibrium. The controller is obtained from the solution of linear matrix inequalities, which can be solved offline, making the approach suitable for online applications. The proposed methodology offers tools for stability and robustness analysis of deep neural networks interconnected with dynamical systems. |
| title | Controller Design for Bilinear Neural Feedback Loops |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2505.24106 |