Robust Smith Predictor-Based Internal Model Nonlinear Control With Lead Compensation Extended State Observer for PMLSM Servo Systems Considering Time Delay
Yachao Liu, Jian Gao, Yuheng Luo, Lanyu Zhang
Abstract
The time delay in the permanent magnet linear synchronous motor (PMLSM) servo system significantly affects the tracking precision, positioning performance, and anti-interference ability of the system. To address this problem, this article proposes a robust smith predictor (RSP) based internal mode nonlinear controller (IMNC) with a lead compensated estimated state observer (LCESO), which is referred to as the IMC-LCESO-RSP method. The time delay between the control input and the system output is first identified online using the intercorrelation function and the fast Fourier transform algorithm, and an RSP that can match the model uncertainty is designed to accurately compensate the time delay. Based on the known model information and the RSP output signal, an LCESO is constructed to effectively reduce the phase lag of the estimated state. An IMNC that adjusts the gain characteristics according to the magnitude of the feedback error is designed to perform fast tracking and precise positioning of the closed-loop system. The results of the simulations and experiments verified the effectiveness and advancement of the proposed IMNC-LCESO-RSP method, which can perform good tracking and positioning as well as high anti-interference performance of the PMLSM servo systems.