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Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

作     者:Zhi-Jiang Du Li-Min Ren Wei-Dong Wang Wei Dong 

作者机构:State Key Laboratory of Robotics and SystemHarbin Institute of Technology College of Mechanical EngineeringBeihua University 

出 版 物:《Journal of Harbin Institute of Technology(New Series)》 (哈尔滨工业大学学报(英文版))

年 卷 期:2013年第20卷第4期

页      面:121-128页

核心收录:

学科分类:081104[工学-模式识别与智能系统] 08[工学] 0811[工学-控制科学与工程] 

基  金:Sponsored by the National Nature Science Foundation of China(Grant No.61105088) 

主  题:kinematics/fuzzy logic combined formation controller mobile robot backstepping 

摘      要:A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the *** kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the *** fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy *** force and torque acting on robots are described as linguistic variables and also 25 if-then rules are *** addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics *** innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is *** with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed *** simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the ***,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.

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