多算法超螺旋滑模观测器控制的电梯曳引系统  

The Elevator Traction System Controlled by Multivariate Algorithm Super Spiral Sliding Mode Observer

作　　者：韩方阵 李国勇[1] 侯东斌 张阔 

机构地区：[1]太原理工大学,太原030600 [2]西安理工大学,西安710048

出　　处：《微特电机》2017年第9期56-59,共4页Small & Special Electrical Machines

基　　金：国家自然科学基金资助项目(51075291)

摘　　要：为了降低电梯制造成本的同时又不影响运行舒适度,提出了一种基于支持向量机联合粒子群算法优化的变系数超螺旋滑模观测器,用于电梯转子的转速观测。针对经典永磁同步电机模型强耦合、高阶次及非线性等特征,导致传统滑模观测器存在求解难、抖振严重等问题,建立定子电流状态观测器模型,简化求解过程,提高消抖效果。在用超螺旋滑模观测器观测转速时,引进支持向量机对观测器参数进行拟合,得到支持向量机辨识标准模型,在此基础上,用离子群算法再对支持向量机辨识标准模型寻优,有效地提高了运算速度,并降低了观测器对噪声的敏感性。最后,在实验部分验证了所提策略的有效性。To reduce the manufacturing cost while the comfort of the elevator running was hot affected, a super-twis- ting observer with variable gains based on support vector machine combined with particle swarm optimization was proposed. For classical synchronous motor model existing strong coupling, higher-order and non-linear characteristics, resulting in its solution was difficult to obtain and chattering was very serious. In order to overcome these mismatches, a stator current state observer was proposed. While super-twisting observer was used to determinate speed, the support vector machine effective- ly reduce observer sensitivity of the measurement noise. The results of the experimentation indicate that the proposed section strategy is very effective and reliable.

关 键 词：超螺旋滑模观测器 支持向量机 粒子群算法 永磁同步电机 

分 类 号：TM341[电气工程—电机] TM351