Design of Adaptive Sliding Mode Controller for Four-Mecanum Wheel Mobile Robot - Details

Author：

Lu, Xingyang (Lu, Xingyang.) | Zhang, Xiangying (Zhang, Xiangying.) | Zhang, Guoliang (Zhang, Guoliang.) | Jia, Songmin (Jia, Songmin.) (Scholars：贾松敏)

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EI Scopus

Abstract：

In　this　paper,　an　adaptive　sliding　mode　controller　is　designed　for　the　omnidirectional　mobile　robot　with　four　Mecanum　wheels　to　track　the　trajectory.　The　Mecanum　wheel　mobile　robot　has　been　widely　used　in　factories,　hospitals,　families　and　other　workspaces　because　of　its　omnidirectional　ability.　Consider　the　dynamic　model　of　the　omnidirectional　mobile　robot　based　on　Mecanum　wheel　with　uncertainties　and　external　disturbances,　a　neural　network　adaptive　sliding　mode　control　(NNASMC)　strategy　is　proposed,　which　combines　the　techniques　of　Radial　Basis　Function　(RBF)　neural　network　adaptive　control　method　and　sliding　mode　control　method.　Finally,　some　simulation　experiments　are　conducted　in　the　Matlab　environment.　Simulation　results　demonstrate　the　effectiveness　of　the　proposed　control　method.　©　2018　Technical　Committee　on　Control　Theory,　Chinese　Association　of　Automation.

Keyword：

Mobile robots Wheels Machine design Radial basis function networks Controllers Adaptive control systems Sliding mode control MATLAB Functions

Author Community：

[ 1 ] [Lu, Xingyang]Faulty of Information Technology, Beijing University of Technology, Beijing, China
[ 2 ] [Lu, Xingyang]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
[ 3 ] [Lu, Xingyang]Engineering Research Center of Digital Community, Ministry of Education, Beijing, China
[ 4 ] [Zhang, Xiangying]Faulty of Information Technology, Beijing University of Technology, Beijing, China
[ 5 ] [Zhang, Xiangying]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
[ 6 ] [Zhang, Xiangying]Engineering Research Center of Digital Community, Ministry of Education, Beijing, China
[ 7 ] [Zhang, Guoliang]Faulty of Information Technology, Beijing University of Technology, Beijing, China
[ 8 ] [Zhang, Guoliang]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
[ 9 ] [Zhang, Guoliang]Engineering Research Center of Digital Community, Ministry of Education, Beijing, China
[ 10 ] [Jia, Songmin]Faulty of Information Technology, Beijing University of Technology, Beijing, China
[ 11 ] [Jia, Songmin]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, China
[ 12 ] [Jia, Songmin]Engineering Research Center of Digital Community, Ministry of Education, Beijing, China

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Source ：

ISSN： 1934-1768

Year： 2018

Volume： 2018-July

Page： 3983-3987

Language： English

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count： 24

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 4

Affiliated Colleges：

信息学部

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