Neural-Network-Based Contouring Control for Robotic Manipulators in Operational Space
Neural-Network-Based Contouring Control for Robotic Manipulators in Operational Space
复制标题
操作空间中基于神经网络的机器人操纵器轮廓控制
DOI：
10.1109/tcst.2011.2147316
复制
发表时间：
2012-07-01
影响因子：
4.8
通讯作者：
Yang, Chunyu
中科院分区：
文献类型：
--
作者：
Wang, Liangyong;Chai, Tianyou;Yang, Chunyu
This brief presents a contouring control scheme for robotic manipulators. The geometric properties of the desired contour are incorporated in the controller design phase, and the resulting controller has been structured as a two-layered hierarchical control scheme that consists of an outer loop and an inner loop. The outer loop is formed by kinematic control system in operational space, which can be designed to assign different dynamics to the tangential, normal, and binormal direction of the desired contour. It is shown that the outer loop can provide a joint velocity reference signal to the inner one. The inner loop is used to implement a velocity servo control system at the robot joint level. Meanwhile, a radial basis function network is adopted to compensate for the nonlinear dynamics of the robotic manipulator, where a robust control strategy is used to suppress the modeling error of neural networks. Experimental results on the Zebra-Zero robotic manipulator have demonstrated the effectiveness of the proposed control scheme in comparison with other control strategies.
