基于混沌优化算法的磁悬浮开关磁阻电动机控制的研究  

Research of Bearing-Less Switched Reluctance Motor's Control Based on Chaos Optimization Algorithms

作　　者：杨国福[1] 

机构地区：[1]河北科技大学电气信息学院,河北石家庄050018

出　　处：《电工电气》2009年第7期4-6,27,共4页Electrotechnics Electric

基　　金：国家自然科学基金资助项目(50477030)

摘　　要：针对磁悬浮开关磁阻电动机控制系统高精确度、快响应的要求,阐述了基于混沌优化算法的模糊神经网络控制方案。采用混沌粗搜索与细搜索相结合的优化策略,对模糊神经网络控制器中的参数进行优化,给出了具体设计方法和优化步骤。仿真结果表明,该磁悬浮开关磁阻电动机控制系统无振荡、无超调,具有较高的精度、较强的鲁棒性和抗干扰能力。Aiming at the requirements of high accuracy and fast response of bearing-less switched reluctance motor＇s control system, the control project of fuzzy neural network （FNN） based on chaos optimization algorithms was expounded. The parameters of FNN controller were optimized with the chaos optimization tactics which adopted the combination of thick searching and thin searching, the concrete device methodology and optimization steps given. Emulation effects show that this bearing-less switched reluctance motor＇s control system has no vibration and overshoot with high accuracy, strong robustness and anti-disturbance.

关 键 词：磁悬浮开关磁阻电动机 模糊神经网络 混沌优化算法 

分 类 号：TM352[电气工程—电机]