Adaptive reaching law sliding mode position control of PMLSM based on nonlinear dynamics model

In order to solve the problem of uncertain factors such as friction, cogging force, parameter mismatch, and external disturbances affecting the position tracking performance of permanent magnet linear synchronous motor (PMLSM), an adaptive reaching law sliding mode control (ARLSMC) method based on nonlinear dynamic model was proposed. Due to the fact that cogging force and friction are the main nonlinear dynamics in the system, and their model parameters vary with the position of the PMLSM rotor, an accurate model based on non-uniform rational B-spline (NURBS) functions was designed to provide a model basis for the design of motor control systems. Secondly, the ARLSMC method was designed to suppress the influence of uncertainty factors on the system. The adaptive convergence law used in ARLSMC can change in real time with the size of position error, which can improve convergence speed while reducing system chattering and improving position tracking accuracy. To further enhance robustness of the system to uncertainty, a sliding mode disturbance observer (SMDO) was designed to estimate the disturbance value in real time and feedforward compensate the estimated value to the control law of ARLSMC. Finally, feasibility and effectiveness of the proposed method in improving position tracking performance and robustness of the PMLSM servo system were verified through simulation and experimentation. © 2024 Editorial Department of Electric Machines and Control. All rights reserved.