In an attempt to solve the problem of the many parameters of the traditional active disturbance rejection controller (ADRC) and to accurately estimate the mover position and speed required by a permanent magnet synchronous linear motor (PMLSM) system, an improved ADRC and a novel nonsingular fast terminal sliding mode observer (NFTSMO) are proposed. Firstly, the traditional first-order ADRC is simplified, the tracking differentiator (TD) module is removed, and the direct error is used to replace the nonlinear function in the extended state observer (ESO) and nonlinear state error feedback (NLSEF) module. Based on the traditional NFTSMO, the smooth back electromotive force (EMF) is obtained by adding the TD to reduce the phase delay caused by the low-pass filter in the traditional sliding mode observer (SMO), and the actuator position and speed information are modulated from the observed back EMF based on the principle of a phase-locked loop (PLL). Simulation and experiments show that this method not only simplifies the system structure of PMLSM but also optimizes many parameters in ADRC while retaining the original excellent performance. Compared with the traditional NFTSMO, the improved NFTSMO enhances the observation accuracy, reduces the chattering phenomenon of the system, and improves the robustness of the system.

To enhance the control performance of a permanent magnet linear synchronous motor (PMLSM) and to improve its dynamic response performance and steady-state accuracy, a PMLSM model predictive integrated control (MPC) system based on a super-twisting sliding mode observer (ST-SMO) is proposed. According to the mathematical model of a PMLSM, this paper designs a three-step model to predict the comprehensive control correction factor, optimize the prediction speed and current, reduce the response time, and enhance the system’s stability. Meanwhile, in order to solve the problem of the PMLSM’s high dependence on mechanical sensors, the ST-SMO is introduced to observe the rotation speed of PMLSM, which has better tracking performance and observation accuracy than a traditional sliding mode observer (SMO). Finally, the experimental verification is carried out on the PMLSM experimental platform. The software simulation and hardware experiment results show that the control system designed in this paper not only simplifies the overall structure of the system, but it also has better control performance and tracking ability. Compared with traditional control methods and SMO, it has better control performance, stability, and speed-tracking performance.