Tuning of electric drive speed controllers is complicated by nonlinearities. Usual practice obtains controller settings with conventional linear analysis methods and then tunes the settings using trial-and-error methods during commissioning. An alternative approach, using genetic algorithms for the online tuning, is proved experimentally to optimize the drive's response efficiently. These settings are critically dependent on operating point.
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Silva et al. (2000) studied this question.
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