Stability Margins of Neural Network Controllers
<|reference_start|>Stability Margins of Neural Network Controllers: 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.<|reference_end|>
@article{junnarkar2024stability,
    title={Stability Margins of Neural Network Controllers},
    author={Neelay Junnarkar, Murat Arcak, Peter Seiler},
    journal={arXiv preprint arXiv:2409.09184},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.09184},
    primaryClass={eess.SY cs.SY}
}