CACA优化的滑模观测器在IPMSM调速中的应用  

Application of Sliding-Mode Observer CACA Optimized in IPMSM Speed Regulation

作　　者：任娇 REN Jiao(School of Intelligent Manufacturing and Transportation,Urban Vocational College of Sichuan,Chengdu 610000,China)

机构地区：[1]四川城市职业学院智能制造与交通学院,成都610000

出　　处：《吉林大学学报（信息科学版）》2021年第3期310-317,共8页Journal of Jilin University（Information Science Edition）

摘　　要：针对传统滑模观测器抖振现象严重且控制速度慢等问题,利用蚁群算法优化滑模观测控制器。为提高蚁群算法的搜索速度以及全局最优解的寻优能力,将混沌思想与蚁群算法相结合并对其进行优化,同时对改进的混沌蚁群算法优化滑模观测器的增益进行优化,以提高基于滑模观测器控制的内埋式永磁同步电动机转速控制系统的动态响应特性和转速估计精度。最后通过仿真对所提出的改进方法进行验证,结果表明基于混沌蚁群算法优化的转速控制系统在转速控制方面具有更快的响应速度,更低的转速估算误差以及更好的稳态精度,充分说明该方法的有效性。Aiming at the problems of serious chattering and slow control speed of traditional sliding-mode observers,the ant colony algorithm is used to optimize the sliding mode observation controller. In order to improve the search speed and the global optimal solution optimizing ability of ant colony algorithm,the chaos idea is combined with ant colony algorithm. And the improved chaotic ant colony algorithm is used to optimize the gain of the sliding-mode observer to advance dynamic response characteristics and speed estimation accuracy of IPMSM( Interior Permanent Magnet Synchronous Motor) speed control system. Finally,the method proposed is verified by simulation. The simulation results show that this speed control system has faster response speed,lower speed estimation error and better steady-state accuracy in speed control. The effectiveness of this method is fully demonstrated.

关 键 词：转速控制 内埋式永磁同步电机 滑模观测器 混沌蚁群算法 

分 类 号：TM351[电气工程—电机]