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

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，进行了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。

 

Vibration control of a Rotating Two-connected Flexible Beam using RBF-based self-adaptive fuzzy neural network

The coupled rigid and flexible system that connects rigid hub and flexible attachment through flexible joint is widely applied in areas like satellite solar panels and space robot. The vibration generating by slewing and external disturbance excitation will affect the stability and pointing accuracy of the system, while more vulnerable to flexible structure with connected parts. Experimental setup of the rotating two-connected flexible beam is designed and built up, and vibration frequency response feature analysis based on piezoelectric sensor signal is conducted. The PD algorithm and proposed RBF-based self-adaptive fuzzy neural network algorithm are applied to AC servo motor actuator for conducting the set-point active vibration control experiments. Experimental results show that vibrations are significantly suppressed when applying the proposed RBF-based self-adaptive fuzzy neural network algorithm.