{'fraction_non_alphanumeric': 0.018779342723004695, 'fraction_numerical': 0.0018779342723004694, 'mean_word_length': 5.62111801242236, '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}}
Gain-scheduled flight control law design using a new fuzzy clustering technique

In this paper a gain scheduling methodology is proposed, which exploits a fuzzy modeling technology based on quasi-linear parameter varying (QLPV) description of a nonlinear model of a missile, to resolve two main deficiencies of classical gain scheduling approaches (restriction to near equilibrium operation and lack of a satisfactory interpolation mechanism). A new clustering approach (designated as fuzzy clustering based classification trees: FC2T) is employed in fuzzy modeling. It is shown that employment of FC2T in the development of fuzzy model for the system produces a lower estimation error than Gustafson-Kessel fuzzy clustering and a tree partitioning algorithm, while it does not confront by randomly initialization problem. Merits of the proposed fuzzy model-based gain scheduling technique are demonstrated in a demanding application. Simulation studies are reported to demonstrate the stability, the performance and the robustness of the designed fuzzy controller.