Learning control of nonhonolomic robot based on support vector machine

被引：0

作者：

冯勇 ^{[1
,2
]}

葛运建 ^{[2
]}

曹会彬 ^{[2
]}

孙玉香 ^{[2
]}

机构：

[1] Department of Automation,University of Science and Technology of China

[2] Institute of Intelligent Machine,Chinese Academy of Science

来源：

JournalofCentralSouthUniversity | 2012年 / 19卷 / 12期

基金：

中国国家自然科学基金;

关键词：

nonhonolomic robot; learning control; support vector machine; nonlinear control law; dynamic control;

D O I：

暂无

中图分类号：

TP18 [人工智能理论]; TP242 [机器人];

学科分类号：

081104 ; 0812 ; 0835 ; 1111 ; 1405 ;

摘要：

A learning controller of nonhonolomic robot in real-time based on support vector machine(SVM)is presented.The controller includes two parts:one is kinematic controller based on nonlinear law,and the other is dynamic controller based on SVM.The kinematic controller is aimed to provide desired velocity which can make the steering system stable.The dynamic controller is aimed to transform the desired velocity to control torque.The parameters of the dynamic system of the robot are estimated through SVM learning algorithm according to the training data of sliding windows in real time.The proposed controller can adapt to the changes in the robot model and uncertainties in the environment.Compared with artificial neural network(ANN)controller,SVM controller can converge to the reference trajectory more quickly and the tracking error is smaller.The simulation results verify the effectiveness of the method proposed.

引用

页码：3400 / 3406

页数：7

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