{'fraction_non_alphanumeric': 0.011434511434511435, 'fraction_numerical': 0.0, 'mean_word_length': 5.253246753246753, '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}}
A fuzzy controller for idle speed regulation

Fuzzy control is characterized by the treatment of vague control rules. For the serious application of such rule systems it is of major importance to clarify their semantic background. How essential these considerations are, is reflected by the fact that the way engineers use fuzzy control does often not coincide with the widespread understanding of control rules as logical statements or implications. Therefore fuzzy control should rather be seen as an interpolation of a partially specified control function in a vague environment, reflecting the indistinguishability of measurements or control values. In this paper we outline that the concept of equality relations is a natural way to represent such vague environments. Furthermore we show how our resulting view of fuzzy control has successfully been applied to develop a well-founded (generalized) fuzzy controller for idle speed regulation of a car engine.