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Research of brushless DC motor control system based on RBF neural network

机译:基于RBF神经网络的无刷直流电机控制系统研究。

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Brushless DC motor (BLDCM) with non-linear, strong coupling and other advantages are widely used in various occasions. Aiming at the shortcomings of low precision and poor robustness of conventional PID brushless DC motor controller, a brushless DC motor control system based on RBF neural network is designed by analyzing the mathematical model of BLDCM. The simulation results show that compared with the conventional PID control method, this method can greatly improve the dynamic characteristics of the control system and reduce the steady-state error of the system, so as to improve the system's adaptive ability and anti-jamming capability, To meet the system requirements for control performance.
机译:具有非线性,强耦合等优点的无刷直流电动机(BLDCM)广泛用于各种场合。针对传统PID无刷直流电动机控制器精度低,鲁棒性差的缺点,通过分析BLDCM的数学模型,设计了一种基于RBF神经网络的无刷直流电动机控制系统。仿真结果表明,与传统的PID控制方法相比,该方法可以大大改善控制系统的动态特性,减少系统的稳态误差,从而提高系统的自适应能力和抗干扰能力,满足系统对控制性能的要求。

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