Robust Learning-Based Control via Bootstrapped Multiplicative Noise

24 Feb 2020 Benjamin Gravell Tyler Summers

Despite decades of research and recent progress in adaptive control and reinforcement learning, there remains a fundamental lack of understanding in designing controllers that provide robustness to inherent non-asymptotic uncertainties arising from models estimated with finite, noisy data. We propose a robust adaptive control algorithm that explicitly incorporates such non-asymptotic uncertainties into the control design... (read more)

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