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提出了一种基于 Sugeno模糊推理神经网络位置控制器 ,以永磁无刷直流电机 ( BLDCM)构成伺服系统作为对象进行了仿真实验 ,研究了该控制器的学习精度、收敛速度及控制性能 ,仿真结果表明本文所设计模糊神经网络位置控制器学习精度高、收敛速度快、在系统同时存在电机参数的变化和负载扰动时 ,具有较强的鲁棒性和抗干扰能力。
A position controller based on Sugeno fuzzy inference neural network is proposed. The servo system of the BLDCM is simulated and studied. The learning accuracy, convergence speed and control performance of the controller are studied. The simulation The results show that the fuzzy neural network controller designed in this paper has high learning precision and fast convergence speed. It has strong robustness and anti-jamming capability when the system has both the changes of motor parameters and load disturbances.