Stability Margins of Neural Network Controllers
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913174433824768 |
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| author | Junnarkar, Neelay Arcak, Murat Seiler, Peter |
| author_facet | Junnarkar, Neelay Arcak, Murat Seiler, Peter |
| contents | We present a method to train neural network controllers with guaranteed stability margins. The method is applicable to linear time-invariant plants interconnected with uncertainties and nonlinearities that are described by integral quadratic constraints. The type of stability margin we consider is the disk margin. Our training method alternates between a training step to maximize reward and a stability margin-enforcing step. In the stability margin enforcing-step, we solve a semidefinite program to project the controller into the set of controllers for which we can certify the desired disk margin. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_09184 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stability Margins of Neural Network Controllers Junnarkar, Neelay Arcak, Murat Seiler, Peter Systems and Control We present a method to train neural network controllers with guaranteed stability margins. The method is applicable to linear time-invariant plants interconnected with uncertainties and nonlinearities that are described by integral quadratic constraints. The type of stability margin we consider is the disk margin. Our training method alternates between a training step to maximize reward and a stability margin-enforcing step. In the stability margin enforcing-step, we solve a semidefinite program to project the controller into the set of controllers for which we can certify the desired disk margin. |
| title | Stability Margins of Neural Network Controllers |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2409.09184 |