Provided is a permanent-magnet synchronous motor random-filtering neural network control method which takes iron loss into consideration, belonging to the technical field of permanent-magnet synchronous motor position-tracking control. The method addresses the control accuracy requirements of permanent magnet synchronous motors and the problem of random disturbance and nonlinearity in drive systems; in conventional backstepping methods, a command filtering technology is introduced to solve the problem of 'calculation explosion' in the calculation process; at the same time, a neural network is used to approximate the nonlinear function in the system and construct a neural network adaptive position tracking controller. The invention ensures that the tracking error of the system can converge to within a sufficiently small neighborhood of the origin, has higher operating efficiency, stronger interference resistance capability, and better control performance.
PERMANENT-MAGNET SYNCHRONOUS MOTOR RANDOM-FILTERING NEURAL NETWORK CONTROL METHOD WHICH TAKES IRON LOSS INTO CONSIDERATION