基于自适应RBF模糊神经网络的旋转柔性铰接梁的振动控制  

Vibration control of a rotating two-connected flexible beam using RBF-based self-adaptive fuzzy neural network

作　　者：邱志成[1] 许燕飞[1] 

机构地区：[1]华南理工大学机械与汽车工程学院,广州510641

出　　处：《振动与冲击》2016年第7期89-95,共7页Journal of Vibration and Shock

基　　金：国家自然科学基金资助项目(51175181);华南理工大学中央高校基本科研业务费专项资金资助项目(2014ZG0019)

摘　　要：由柔性关节连接中心刚体和挠性附件的刚柔耦合系统广泛应用于卫星太阳能帆板、空间机器人等领域中,在调姿或者外部扰动带来振动时,将影响系统的稳定性和指向精度,对带有铰接结构的柔性梁的影响更甚。设计并建立了带有柔性关节(谐波齿轮)的旋转柔性铰接梁实验平台,基于压电传感器测量信号的振动频响特性分析,分别采用PD控制和自适应RBF模糊神经网络控制算法,进行了基于电机驱动的位置设定点弯曲振动的主动控制研究。实验比较结果验证设计的自适应RBF模糊神经网络控制算法能够快速抑制振动。A rigid-flexible coupled system connecting a rigid hub and flexible attachments with flexible joints is widely applied in areas like satellite solar panels and space robots. The system＇s vibration induced by slewing and external disturbance excitation affects the stability and pointing accuracy of the system,it affects flexible beams with jointed parts more strongly. Here,test rig of a rotating two-connected flexible beam was designed and built,and the vibration frequency response feature analysis based on piezoelectric sensor signals was conducted. PD control and the RBF-based self-adaptive fuzzy neural network algorithm were adopted to perform the set-point active vibration control of an AC servo motor actuator.Experimental results showed that its vibration is rapidly suppressed when applying the proposed RBF-based self-adaptive fuzzy neural network algorithm.

关 键 词：刚柔耦合系统 柔性铰接梁 振动主动控制 自适应 模糊神经网络 

分 类 号：TH212[机械工程—机械制造及自动化] TP241[自动化与计算机技术—检测技术与自动化装置]