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- W2483995005 abstract "Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework which connects these approaches. Experimental results on an industrial motion system validate the approaches and illustrate benefits of rational feedforward tuning in motion systems, including pre- and post-actuation through stable inversion." @default.
- W2483995005 created "2016-08-23" @default.
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- W2483995005 date "2016-07-01" @default.
- W2483995005 modified "2023-09-25" @default.
- W2483995005 title "Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison" @default.
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- W2483995005 doi "https://doi.org/10.1109/acc.2016.7525313" @default.
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