Neural network real-time IP position controller on-line design for permanent magnetic linear synchronous motor

This paper presents a real-time IP position controller realized by neural network for permanent magnetic linear synchronous motor (PMLSM) servo system. The,proposed neural network, whose weight has definitely material meaning, is simple and can be rapidly adjusted on-line, and the real-time position control for PMLSM is accomplished. In order to improve the robustness and the control precision of PMLSM drive system, the mover mass, viscous damping factor and disturbance force are estimated by the proposed estimator, which is composed of a recursive least-squares estimator (RLSE) and a disturbance force observer A simulation demonstrates that the proposed IP controller makes the system more robust to the uncertain load and the variation of the parameters.