基于单神经元自适应的五相SRM直接转矩控制

Direct Torque Control of Five-phase Switched Reluctance Motor Based on Single Neuron Adaptive

针对开关磁阻电机严重的非线性和大的转矩脉动等问题,选用五相电机为研究对象,对直接转矩控制方法进行了分析与研究,提出了一种单神经元自适应PID与传统PI复合的新型控制策略。通过速度误差限进行快速切换,在大速度误差下利用神经元自学习能力输出可调PID参数控制调速,小速度误差下采用传统PI控制调速,使系统误差快速减小并保持稳定。对控制系统进行了仿真实验,仿真结果表明,这种控制策略能够有效减小转矩脉动,调速性能优秀,并且避免了电机非线性、多变量、强耦合等问题,系统动静态性能良好。

Aiming at the serious nonlinear and large torque ripple of switched reluctance motor(SRM),five phase motor is selected as the research object, and the direct torque control method is analyzed and studied.A new control strategy of single neuron adaptive PID combined with traditional PI is proposed, which can switch quickly through the speed error limit, In the case of large speed error, the neuron self-learning ability is used to output adjustable PID parameters to control the speed regulation.In the case of small speed error, the traditional PI control is used to control the speed regulation, so that the system error can be quickly reduced and kept stable.The simulation results show that this control strategy can effectively reduce the torque ripple, and has excellent speed regulation performance, and avoid the nonlinear, multivariable, strong coupling and other problems of the motor.The dynamic and static performance of the system is good.