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Many controlled systems suffer from unmodeled nonlinear effects that recur periodically over time. Model-free controllers generally cannot compensate these effects, and good physical models for such periodic dynamics are challenging to construct. We investigate nonparametric system identification for periodically recurring nonlinear effects. Within a Gaussian process (GP) regression framework, we...
Screws and gears are a source of periodically recurring nonlinear effects in mechanical dynamical systems. Unless the state sampling frequency is much higher than the periodic effect, model-free controllers cannot always compensate these effects, and good physical models for such periodic dynamics are challenging to construct. We investigate nonparametric system identification with an explicit focus...
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