Robotic trajectory tracking control method based on reinforcement learning

被引：0

作者：

Liu W. ^{[1
]}

Xing G. ^{[2
]}

Chen H. ^{[1
]}

Sun H. ^{[1
]}

机构：

[1] School of Control Science and Engineering, Hebei University of Technology, Tianjin

[2] School of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2018年 / 24卷 / 08期

关键词：

Feedforward neural network; PD controller; Reinforcement learning; Robot; Trajectory tracking;

D O I：

10.13196/j.cims.2018.08.011

中图分类号：

学科分类号：

摘要：

To improve the working performance of robotic trajectory tracking controller, the robotic trajectory tracking control method based on reinforcement learning was proposed. The basic principle of reinforcement learning was introduced, and then the robot trajectory tracking control strategy based on SARSA was proposed. By using the reinforcement learning, the unknown disturbance factors were compensated and the adaptability to the unknown was improved after the PD control method was applied. The experimental results verified the feasibility and effectiveness of the reinforcement learning method in the trajectory tracking problem of robot arms, and the learning speed of the controller was enhanced. © 2018, Editorial Department of CIMS. All right reserved.

引用

页码：1996 / 2004

页数：8

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