Dynamic triangular neural controller for stepper motor trajectory tracking

We present a novel neural controller for a stepper motor. This controller is developed as follows. Modifying published results for nonlinear identification using dynamic neural networks (NNs), an NN identifier of triangular form is implemented. Then, based on this mode, a control law using sliding modes is derived. This neural identifier and the proposed control law allow trajectory tracking for stepping motors. Applicability of the approach is tested via simulations.