{'fraction_non_alphanumeric': 0.02038216560509554, 'fraction_numerical': 0.0, 'mean_word_length': 5.442622950819672, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Fictitious Reference Iterative Tuning of Disturbance Observers for Attenuation of the Effect of Periodic Unknown Exogenous Signals

Abstract In this paper, we develop a data-driven controller tuning for the disturbance observers. Particularly, we focus on the disturbance attenuation problem for a periodic unknown disturbance. However, in the case where it is difficult to construct inverse mathematical model of a plant which is implemented in the disturbance observer, we have to tale much time and costs for identification. In order to overcome such a difficulty, we utilize fictitious reference iterative tuning (FRIT), which is data-driven controller tuning with only one-shot experimental data, for tuning of parameters of controllers to eliminate the effect of the disturbance.