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Robustness and Consistency in Linear Quadratic Control with Untrusted Predictions

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Published:28 February 2022Publication History
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Abstract

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.

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