HIGHLIGHTS
- who: C. De Persis et al. from the (UNIVERSITY) have published the paper: Learning Controllers from Data via Approximate Nonlinearity Cancellation, in the Journal: (JOURNAL)
- what: This allows the authors to explicitly determine region of attractions and invariant sets (and to try to maximize such sets by minimising the remainder, which is what the authors attempt to do through nonlinearity cancellation). The authors show how the approach can accommodate the presence of process disturbances not only during the data collection phase, but also during the execution of the control task and provide estimates of robustly . . .
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