{'fraction_non_alphanumeric': 0.028645833333333332, 'fraction_numerical': 0.0, 'mean_word_length': 5.05511811023622, '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}}
Data-driven IMC for non-minimum phase systems - Laguerre expansion approach -

This paper proposes a data-driven parameter tuning of the internal model controller (IMC) for non-minimum phase plants. In order to perform the parameter tuning of the IMC, we utilize the fictitious reference iterative tuning (FRIT), which enables us to obtain the desired parameter of the controller with only one-shot experiment data. Particularly, we propose an embedding of the internal mathematical model which is described by Laguerre expansion for describing non-minimum phase plants. Moreover, we show that the proposed approach enables us to obtain not only a desired controller but also a well-approximated mathematical model of the actual non-minimum phase plant simultaneously.