# Robustness and Consistency in Linear Quadratic Control with Predictions

@article{Li2021RobustnessAC, title={Robustness and Consistency in Linear Quadratic Control with Predictions}, author={Tongxin Li and Ruixiao Yang and Guannan Qu and Guanya Shi and Chenkai Yu and Adam Wierman and Steven H. Low}, journal={ArXiv}, year={2021}, volume={abs/2106.09659} }

We study the problem of learning-augmented predictive linear quadratic control. Our goal is to design a controller that balances consistency, which measures the competitive ratio when predictions are accurate, and robustness, which bounds the competitive ratio when predictions are inaccurate. We propose a novel λconfident controller and prove that it maintains a competitive ratio upper bound of 1 +min{O(λ2ε) +O(1− λ)2, O(1) +O(λ2)} where λ ∈ [0, 1] is a trust parameter set based on the… Expand

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