二自由度可重构机械臂轨迹跟踪控制  

Trajectory tracking control of 2-DOF modular manipulator

作　　者：张振国 李岩[1] 刘克平[1] ZHANG Zhenguo;LI Yan;LIU Keping(School of Electrical & Electronic Engineering, Changchun University of Technology, Changchun 130012, China)

机构地区：[1]长春工业大学电气与电子工程学院,吉林长春130012

出　　处：《长春工业大学学报》2020年第6期550-557,共8页Journal of Changchun University of Technology

基　　金：吉林省自主创新能力建设专项(2019C010)。

摘　　要：采用RBF神经网络学习方法预测交联项、摩擦项以及干扰项,用以消除模型不确定性影响,并降低控制器增益。为确保MRRs系统的跟踪误差在有限时间内收敛到零,将终端滑模(TSM)算法引入到控制器设计中。利用Lyapunov方法分析了闭环系统的稳定性。最后实验验证了该方法的有效性。Radial basis function(RBF)neural network learning method is used to simulate the interconnect terms,friction and some disturbances to eliminate the uncertainty of the system and decrease the controller gain.To ensure that the tracking error of the MRRs system can converges to zero within a fixed time,the terminal sliding mode(TSM)algorithm is introduced into the controller.The stability of closed-loop system is analysed with Lyapunov method.Simulation experiment is performed.

关 键 词：模块化可重构机械臂 终端滑模控制 RBF神经网络控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]