基于非线性动力学模型的PMLSM自适应趋近律滑模位置控制

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

为了解决摩擦力、定位力、参数失配和外部扰动等不确定性因素影响永磁直线同步电动机(PMLSM)位置跟踪性能的问题,提出基于非线性动力学模型的自适应趋近律滑模控制(ARLSMC)方法。由于定位力和摩擦力是系统中主要的非线性动力学因素,且其模型参数会随PMLSM动子位置而变化,因此设计基于非均匀有理B样条(NURBS)函数的精确模型,为电机控制系统设计提供模型基础。其次,设计ARLSMC方法抑制不确定性因素对系统的影响,ARLSMC中所采用的自适应趋近律可以随位置误差大小实时变化,能够在提高收敛速度的同时减小系统抖振,提高位置跟踪精度。为进一步增强系统对于不确定性的鲁棒性,设计滑模扰动观测器(SMDO)实时估计扰动值并将估计值前馈补偿到ARLSMC的控制律。最后,通过仿真和实验验证本文方法在提高PMLSM伺服系统的位置跟踪性能和鲁棒性能方面的可行性和有效性。

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.