{'fraction_non_alphanumeric': 0.005235602094240838, 'fraction_numerical': 0.0, 'mean_word_length': 5.828571428571428, '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}}
Analysis and efficient implementation of fuzzy logic control algorithms

Fuzzy logic is presently used to synthesize single layer nonlinear control systems in an increasing range of application areas. The proper role for fuzzy logic is within the framework of a hierarchically structured control system that may incorporate conventional control strategies. The paper focuses on integration of these notions within an analytically tractable framework whereby certain fundamental system theoretic properties such as stability and robustness to modeling uncertainty can at least in principle be verified. The proposed approach is based on large scale systems theory and incorporates nonlinear singular perturbation in an analytical study of hierarchically structured control systems as well as the notion of Kalman filter based optimal system identification. Theorems regarding the behavior of such systems are presented and their implications are discussed.