期刊
NEUROCOMPUTING
卷 140, 期 -, 页码 8-18出版社
ELSEVIER
DOI: 10.1016/j.neucom.2014.03.041
关键词
Consensus; Multiple robotic manipulators; Leader-follower; Radial basis function; Neural network
资金
- National Nature Science Foundation of China [61004080, 61273188]
- Shandong Provincial Natural Science Foundation [ZR2011FM003]
- Jiangxi Provincial Education Department of China, China [GJJ12132]
- Fundamental Research Funds for the Central Universities of China
- Development of key technologies project of Qingdao Economic and Technological Development Zone [2011-2-52]
- Taishan Scholar Construction Engineering Special funding
A framework for neural networks (NN) based consensus control is proposed for multiple robotic manipulators systems (MRMS) under leader-follower communication topology. Two situations, that is, fixed and switching communication topologies, are studied by using adaptive and robust control principles, respectively. Radial basis function (RBF) NN enhances estimator and observer are developed to estimate system uncertainty and obtain the leader manipulator's control torque online. By using the Lyapunov stability theory, an adaptive consensus control algorithm is designed to tune the weight of the RBF NN online, which can stabilize the consensus error to a small residual set. On this basis, a novel robust control algorithm is presented to eliminate the estimating errors caused by RBF NN, which can achieve asymptotical stability. The stability of the proposed approaches is analyzed by using Lyapunov methods. Finally numerical bench tests are conducted to validate the effectiveness of the proposed approach. (C) 2014 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据