Based on Chaos Neural Network Vector Control for Permanent Magnet Synchronous Motors

between current, voltage, and rotor position on the stationary coordinate axis of a permanent magnet synchronous motor is a common method for vector control of the motor. The online training algorithm of the network is simple, the system response is fast, and it exhibits good adaptability. Building upon this, a hybrid approach combining chaos optimization and gradient descent is employed for the offline training of the BP neural network, which is subsequently utilized for vector control of the permanent magnet synchronous motor.