{'fraction_non_alphanumeric': 0.01768867924528302, 'fraction_numerical': 0.0, 'mean_word_length': 5.383458646616542, '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}}
Less Conservative Observer-Based Output Feedback MPC for T-S Fuzzy System With Data Loss and Bounded Disturbance

In this paper, we study the performance of model prediction system(MPC) when data is missing and unpredictable disturbances occur. Compared the recent result in the literature, the proposed observer-based output feedback MPC is designed by the aid of developing a new switching idea. At each sampling instant, the considered optimization problem is transformed into an online minimization of the infinite time domain performance index function. More importantly, the developed switching idea is well carried out by exploiting the newly updated information and a better control performance can be achieved in this paper. Finally, the comparison of simulation graphics proves that the proposed method has better performance than before.