Neural-Learning-Based Control for a Constrained Robotic Manipulator with Flexible Joints
Wei He; Zichen Yan; Yongkun Sun; Yongsheng Ou; Changyin Sun
刊名IEEE Transactions on Neural Networks and Learning Systems
2018
文献子类期刊论文
英文摘要Nowadays, the control technology of the robotic manipulator with flexible joints (RMFJ) is not mature enough. The flexible-joint manipulator dynamic system possesses many uncertainties, which brings a great challenge to the controller design. This paper is motivated by this problem. In order to deal with this and enhance the system robustness, the full-state feedback neural network (NN) control is proposed. Moreover, output constraints of the RMFJ are achieved, which improve the security of the robot. Through the Lyapunov stability analysis, we identify that the proposed controller can guarantee not only the stability of flexible-joint manipulator system but also the boundedness of system state variables by choosing appropriate control gains. Then, we make some necessary simulation experiments to verify the rationality of our controllers. Finally, a series of control experiments are conducted on the Baxter. By comparing with the proportional–derivative control and the NN control with the rigid manipulator model, the feasibility and the effectiveness of NN control based on flexible-joint manipulator model are verified.
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语种英语
内容类型期刊论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/13674]  
专题深圳先进技术研究院_集成所
推荐引用方式
GB/T 7714
Wei He,Zichen Yan,Yongkun Sun,et al. Neural-Learning-Based Control for a Constrained Robotic Manipulator with Flexible Joints[J]. IEEE Transactions on Neural Networks and Learning Systems,2018.
APA Wei He,Zichen Yan,Yongkun Sun,Yongsheng Ou,&Changyin Sun.(2018).Neural-Learning-Based Control for a Constrained Robotic Manipulator with Flexible Joints.IEEE Transactions on Neural Networks and Learning Systems.
MLA Wei He,et al."Neural-Learning-Based Control for a Constrained Robotic Manipulator with Flexible Joints".IEEE Transactions on Neural Networks and Learning Systems (2018).
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