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提出一种基于神经网络智能控制的直接转矩控制系统,神经网络控制是智能控制一个重要的分支,它能够处理非线性、不确定性等问题,具有强大的学习能力。利用神经网络控制代替传统直接转矩控制中的矢量优化选择表,神经网络控制能够迅速、准确地选择逆变器的开关状态。仿真结果表明,基于神经网络控制的直接转矩控制系统能够改善系统非动态、稳态性能。
A direct torque control system based on neural network intelligent control is proposed. Neural network control is an important branch of intelligent control. It can deal with nonlinear and uncertainty problems and has a strong learning ability. Using neural network control instead of vector optimization selection table in traditional direct torque control, neural network control can quickly and accurately select the switching state of the inverter. The simulation results show that the direct torque control system based on neural network control can improve the non-dynamic and steady-state performance of the system.