摘要
在分析研究空间矢量脉宽调制(SVPWM)原理及应用的基础上,设计了一种基于人工神经网络(ANN)的SVPWM控制器。该控制器充分利用ANN快速并行处理能力、学习能力和容错能力,以减少谐波成分及其损耗,降低电机转矩脉动,提高感应电机矢量控制系统的动稳态性能。通过与传统的SVPWM矢量控制系统的仿真分析比较,表明了基于该控制器的调速系统,具有更低的谐波成分和更好的稳态性能及鲁棒性。
The basic principle and application of space vector pulse-width-modulation （SVPWM） was analyzed, and a novel algorithm SVPWM based on the artificial neural network（ANN） was proposed. Because it takes full advantage of the parallel computation, learning and fault-tolerance capability of ANN, the harmonic, harmonic loss of motor and torque ripple have been reduced, and the dynamic and static property of space vector controlled induction motor drive system has been improved. The simulation results verify that the induction motor drive system based on ANN-SVPWM has more perfect performance than that based on conventional space vector controller in static and dynamic property, such as robustness as well as in lower-harmonic.
出处
《电气自动化》
2009年第3期6-8,16,共4页
Electrical Automation
基金
上海市科技创新基金资助项目(08YZ100)
