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• W4327808816 abstract "In this paper, we propose a data-driven approach to derive explicit predictive control laws. The key idea of the presented strategy is to exploit the prior knowledge that the optimal solution is a piece-wise affine controller. As the proposed method allows us to automatically retrieve also a model of the closed-loop system, we show that we can apply classical Lyapunov techniques to perform a prior stability check for safe controller deployment. The effectiveness of the proposed strategy is assessed on a benchmark simulation example, through which we also discuss the use of regularization and preprocessing techniques to handle the presence of noise." @default.
• W4327808816 created "2023-03-19" @default.
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• W4327808816 date "2023-01-01" @default.
• W4327808816 modified "2023-09-23" @default.
• W4327808816 title "Data-Driven Design of Explicit Predictive Controllers With Structural Priors" @default.
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• W4327808816 doi "https://doi.org/10.1109/lcsys.2023.3258913" @default.
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