【摘要】 针对永磁同步牵引电机因参数摄动不确定因素造成控制性能下降以及速度传感器存在成本高、环境要求严格、估计精度不足等问题，提出了一种基于自适应广义高阶平方根容积卡尔曼滤波算法（ASRGHCKF）无速度传感器的永磁同步电机（PMSM）自适应非奇异快速终端滑模控制算法。首先，建立参数摄动下PMSM数学模型；其次，基于扩展滑模扰动观测器（ESMDO）设计自适应非奇异快速终端滑模转速控制算法（ANFTSMC），选择新型指数趋近律可随系统距离滑模面的远近自适应调整趋近速度，同时ESMDO实时精准观测系统的未知扰动部分；最后，结合ASRGHCKF实时精准估计电机的转速和转子位置。通过与PI和传统SMC算法进行仿真和半实物试验对比，验证了该算法在电机参数摄动下暂稳态性能更佳，有利于改善PMSM的无速度传感器控制效果。更多还原

【Abstract】 To solve the degradation in control performance of permanent magnet synchronous motors(PMSMs) due to uncertainties from parameter perturbation, as well as the problems arising from the speed sensor, such as high cost, demanding environmental requirements and deficient accuracy of estimation, this paper proposed an adaptive non-singular fast terminal sliding mode control strategy for PMSMs of sensor-less speed regulation based on the adaptive square root generalized high-order cubature Kalman filter(ASRGHCKF) algorithm. A mathematical model of PMSM was first established under parameter perturbation, and an adaptive non-singular fast terminal sliding mode control algorithm(ANFTSMC) was designed depending on the extended sliding mode disturbance observer(ESMDO). A novel exponential reaching law was selected to adaptively adjust the approach speed depending on the distance of the system from the sliding surface while the unknown disturbance of the system was accurately observed by ESMDO in real time. Finally, the speed and rotor position of the motor were estimated accurately, in combination with ASRGHCKF. Based on the simulation and semiphysical experiment results in comparison with PI control and the traditional sliding mode control(SMC) algorithm, the strategy under the current study was proven with better transient stability performance under motor parameter perturbation, benefiting to improving the sensor-less control effect of PMSM.更多还原