具有外部扰动的参数未知漂浮基柔性空间机械臂的对角递归神经网络控制

讨论载体位置和姿态均不受控情况下,存在外部扰动的参数未知漂浮基柔性空间机械臂系统关节运动的动力学控制问题。由假设模态法,利用拉格朗日方法建立漂浮基柔性空间机械臂的系统动力学方程。以此为基础,针对存在外部扰动和系统参数未知的情况,利用对角递归神经网络逼近柔性空间机械臂系统的逆动力学模型,设计基于对角递归神经网络的控制方案,以控制柔性空间机械臂的关节铰跟踪在关节空间的期望运动轨迹,同时能抑制柔性杆的振动。该方案由于没有专门设计主动控制器抑制柔性振动,因此不需要测量、反馈柔性振动模态,大大简化控制器的结构;无需预知控制对象的精确模型和系统参数,且能克服外部扰动的影响。计算机数值仿真证实所提方案的有效性和可行性。

Diagonal Recurrent Neural Network Control for Free-floating Space Flexible Manipulator with Unknown Parameters and External Disturbance

The dynamic control problem for free-floating space flexible manipulator with unknown parameters and external disturbance in joint space is discussed.With the assumed modes method,the Lagrangian principle is utilized to model the dynamic function of the space flexible manipulator with completely uncontrolled base.Based on above,a diagonal recurrent neural network is used to approximate the inverse dynamic of space flexible manipulator.A control scheme based on diagonal recurrent neural network is designed to dominate the trajectory tracking of joint motion and damp out the vibration of the flexible link.The control scheme does not specially design active controller for flexible vibration suppression,so requires no measurement and feedback of flexible vibration mode,which greatly simplifies the controller structure.Furthermore,the control scheme not only requires no a priori knowledge about the accurate model and system parameters,but also can overcome the affect of external disturbance.A numerical simulation is carried out to illustrate the validity and feasibility of the proposed control scheme.