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Adaptive Controllers for Permanent Magnet Brushless DC Motor Drive System using Adaptive-Network-based Fuzzy Interference System

机译:基于自适应网络的模糊干扰系统的永磁无刷直流电动机驱动系统的自适应控制器

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摘要

Problem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet Brushless DC (BLDC) motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system employing the Adaptive-Network-based Fuzzy Interference System (ANF1S). The nonlinear simulation model of the BLDC motors drive system with ANF1S control based is simulated in the MATLAB/S1MULINK platform. Results: The necessitated data for training the ANF1S control is generated by simulation of the system with conventional PI controller. Conclusion: The simulated electromagnetic torque and rotor speed signify the superiority of the proposed technique over the classical method.
机译:问题陈述:在永磁无刷直流(BLDC)电机驱动系统中,随着负载转矩的变化,自适应速度控制器的参数调整方法会导致响应与设定参考值发生瞬时偏差。方法:本研究首先建立了BLDC驱动系统的数学模型。其次,讨论了采用基于自适应网络的模糊干扰系统(ANF1S)的闭环驱动系统的设计。在MATLAB / S1MULINK平台上仿真了基于ANF1S控制的BLDC电机驱动系统的非线性仿真模型。结果:用于训练ANF1S控制的必要数据是通过使用常规PI控制器对系统进行仿真生成的。结论:仿真的电磁转矩和转子速度表明了该技术优于经典方法的优越性。

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