【摘要】 提出了一种作为无刷直流电动机的速度调节器的参数自校正模糊神经网络控制器.重点研究了模糊控制器的设计、系统增益参数的确定方法和BP神经网络的实现方法.采用双模控制方法,提高了系统的性能.通过数字仿真,证明了采用模糊神经网络控制方法的速度调节器能够提高系统的动、静态特性,减小转矩脉动并使系统具有较强的鲁棒性和抗干扰能力,同时提高了系统的实时性.更多还原

【Abstract】 A parameter self-correction fuzzy neural network controller as a speed control device for a brushless DC electric motor is put forward. The emphasis is placed on the design of the fuzzy controller, the method of determining system′s gain parameter and the method of realizing BP neural network. In order to increase system′s performance, the dual-mode control mode is applied. The digital simulation proved that the speed control device by the fuzzy neural network controlling method can increase dynamic and static state performance of the system, reduce the impulsive motion of torque force, make system have powerful anti-interference capability, and increase performance of the system.更多还原