基于粒子群优化的超声波电机非线性Hammerstein辨识建模  

Identification for USM Non-linear Hammerstein Model Based on Particle Swarm Optimization

作　　者：吕方方[1] 史敬灼[1] 

机构地区：[1]河南科技大学,河南洛阳471003

出　　处：《微电机》2011年第12期17-20,共4页Micromotors

基　　金：河南省基础与前沿技术研究计划(092300410164)

摘　　要：由于超声波电机(USM)具有机电能量转换、不规则外形的定转子以及复杂的摩擦和接触机理,很难建立其适合于控制的非线性数学模型。针对这个问题,本文采用粒子群优化算法建立了超声波电机的非线性Hammerstein模型。该模型由静态非线性和动态线性两部分串联而成,能够以相对简单的形式表述超声波电机的非线性特性。所得模型的仿真计算结果与实验数据接近,表明了建模方法的合理性和所建模型的有效性。The ultrasonic motor （USM） possesses piezoelectric electromechanical energy conversion, an~,ma- lous shape of stator and rotor, complicated mechanism of friction and interface. So the nonlinear model for controlling is difficult to acquire. To this question, this paper gave a non-linear Hammerstein model based on particle swarm optimization. The model is composed of static non-linear part and dynamic linear part, which can describe the non-linear characteristic of USM in a relative simple form. Simulation results of the obtained model are close to measured data, it indicates that the tire. modeling method is reasonable and the model is effec-

关 键 词：超声波电机 非线性模型 粒子群 HAMMERSTEIN模型 

分 类 号：TM359.9[电气工程—电机]