基于粒子群优化的超声波电机非线性Hammerstein辨识建模

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, anoinalous 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 modeling method is reasonable and the model is effective.