{'fraction_non_alphanumeric': 0.011505273250239693, 'fraction_numerical': 0.0, 'mean_word_length': 5.649681528662421, '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}}
Parameters identification and adaptive feedforward control of permanent magnent Linear synchronous motor

This paper proposes a novel adaptive feedforward control strategy based on the parameters identification of a permanent magnent linear synchronous motor (PMLSM). The parameters such as the moving mass and viscous coefficient of a PMLSM are identified through an unbiased least square estimation approach with the employment of current and position signals from the built-in sensors. Based on the identified parameters, the accurate state-space model of the PMLSM is established and a robust feedback controller applying H∞ control method is built. An adaptive feedforward controller based on the nominal model and the online recursion least square method is designed. Simulations and experiments are conducted to verify the control performance of the proposed control system. The results validate that the proposed control approaches are feasible and have better dynamic and tracking performances compared to traditional PID controllers.