Decoupling control for permanent magnet synchronous motor based on single neuron
基于单神经元的永磁同步电机解耦控制

The conventional decoupling strategy for the magnetic field-oriented control of permanent magnet synchronous motors (PMSM) is difficult to achieve high performances. To deal with this problem, we put forward a decoupling control strategy based on the single neuron, by exploiting the independency of neural network on the object model as well as its excellent learning ability. On the basis of the model of traditional magnetic field-oriented control, we build a single neuron decoupling control system for the PMSM, and perform the simulation as well as the experimental tests on the platform with digital signal processor (DSP) as the core element. The experimental results show that the PMSM control system based on the single neuron decoupling has rapid response ability and is almost with no static error and overshoot. It realizes high performance in PMSM control.