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End edge feedback and RBF neural network based vibration control of flexible manipulator

机译:基于末端边缘反馈和RBF神经网络的柔性机械臂振动控制

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摘要

A vision feedback based active vibration control system for flexible manipulator is proposed. Active vibration control is conducted by employing Radial Basis Function (RBF) neural networks to regulate the control parameters of the proportional and derivative (PD) controller. Firstly, the composition of the vision feedback based piezoelectric flexible manipulator system is described. Furthermore, vision based vibration measurement for the flexible manipulator's end side and image processing methods are introduced. Secondly, the system dynamics model is derived by using finite element method, and the equation of the state space representation for the lower mode vibration is provided. Then, the vision feedback based control method is expounded, using RBF neural networks to tune the control parameters dynamically. Finally, simulation and experiments are conducted. The results demonstrate that vision feedback based control system and the RBF neural networks control algorithm can suppress the vibration of the flexible manipulator effectively.
机译:提出了一种基于视觉反馈的柔性机械手主动振动控制系统。主动振动控制是通过使用径向基函数(RBF)神经网络来调节比例和微分(PD)控制器的控制参数的。首先,描述了基于视觉反馈的压电柔性机械手系统的组成。此外,介绍了用于柔性机械手端部的基于视觉的振动测量和图像处理方法。其次,利用有限元方法推导了系统动力学模型,并给出了低模态振动的状态空间表示方程。然后,阐述了基于视觉反馈的控制方法,利用RBF神经网络动态调整控制参数。最后,进行了仿真和实验。结果表明,基于视觉反馈的控制系统和RBF神经网络控制算法可以有效地抑制柔性机械臂的振动。

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