{'fraction_non_alphanumeric': 0.013888888888888888, 'fraction_numerical': 0.0, 'mean_word_length': 5.084415584415584, '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}}
Fuzzy Predictive Control for a Tubular Heat Exchanger System

The paper deals with the problem of controlling the outlet temperature of a tubular heat exchanger system by means of flow pressure. The usual industrial system behavior must precisely be modeled and appropriate control action needs to be obtained based on novel techniques. A new multiple models control strategy using the well-known linear generalized predictive control (LGPC) scheme has been proposed in this paper. Then the best model of the system is accurately identified by an intelligent decision mechanism (IDM) which is organized based on both new recursive weight generator and fuzzy adaptive Kalman filter approaches. Simulations are all done and the results are also compared with those obtained using a nonlinear GPC (NLGPC) approach that is realized based on the Wiener model of the system. The results can verify the validity of the proposed control scheme.