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arXiv · 2101.00488

Non-conservative Design of Robust Tracking Controllers Based on Input-output Data

Liang Xu·Mustafa Sahin Turan·Baiwei Guo·Giancarlo Ferrari-Trecate
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Abstract

This paper studies worst-case robust optimal tracking using noisy input-output data. We utilize behavioral system theory to represent system trajectories, while avoiding explicit system identification. We assume that the recent output data used in the data-dependent representation are noisy and we provide a non-conservative design procedure for robust control based on optimization with a linear cost and LMI constraints. Our methods rely on the parameterization of noise sequences compatible with the data-dependent system representation and on a suitable reformulation of the performance specification, which further enable the application of the S-lemma to derive an LMI optimization problem. The performance of the new controller is discussed through simulations.

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Liang Xu, Mustafa Sahin Turan, Baiwei Guo, Giancarlo Ferrari-Trecate. 2021-06-24. Non-conservative Design of Robust Tracking Controllers Based on Input-output Data. https://arxiv.org/abs/2101.00488

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