A New Intelligent Controller for the Precision Tracking of Permanent Magnet Stepper Motor

A novel intelligent control scheme for the precise tracking of permanent magnet step motor (PMSM) under wide range of motor system parameters is proposed. The scheme consists of an online growing radial basis neural network (RBFNN) controller in parallel with an implicit model adaptive controller for the precise tracking of motor position and speed. The proposed intelligent controller operates in parallel with a fixed parameter PID control law to compensate for the drastic system functional changes. The main advantage of this algorithm is that it is precise, feasible and more effective than other nonlinear adaptive controllers reported to-date. Simulation results are presented in order to show that, positional tracking errors are reduced when the motor parameters are changed drastically while using the proposed control scheme.