基于奇异摄动与神经网络的柔性臂控制

Control of Robot Arms with Link Flexibility Using Singular Perturbation and Neural Network

运用拉格朗日法建立了臂杆柔性的机械臂的动力学方程。为解决柔性臂末端位置的跟踪及克服柔性臂在运动中的振动问题 ,运用奇异摄动法将系统分解成快、慢两个子系统 ,设计混合控制器。通过设计神经网络控制器线性化慢系统 ,使其轨迹跟踪期望值。用线性状态反馈配置极点稳定快系统 ,抑制振动。一个单杆柔性机械臂的仿真算例表明 ,本文的控制方法保证了柔性臂刚性运动的精确跟踪 ,同时消除了弹性振动 。

The dynamic equation of robot arms with link flexibility is established using Lagrange method. To satisfy the tracking requirements of the link-tip position and suppress the oscillation of the link, the singular perturbation approach is used to decompose the robots into a slow subsystem and a fast subsystem, which allows a combined control design for the original system. A neural network controller is designed to linearize the slow subsystem and make the rigid motion track a desired trajectory. Using state-feedback techniques, the poles of the fast subsystem are assigned to stabilize the fast system and attenuate the oscillatory of the link. A simulational example of a single flexible manipulator shows that the combined control is effective in rigid motion tracking control and oscillatory attenuation control, and the unstable zero dynamics can be avoided.