Trajectory Tracking for a 3-DOF Robot Manipulator Based on PSO and Adaptive Neuro-Fuzzy Inference System

被引：0

作者：

Zeng Ke ^{[1
]}

Luo Gui'e ^{[1
]}

Wu Min ^{[2
]}

Lai Xuzhi ^{[2
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China

[2] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China

来源：

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年

基金：

国家高技术研究发展计划(863计划); 中国国家自然科学基金;

关键词：

Trajectory tracking; Robot manipulator; Sliding mode control; Particle swarm optimization; Adaptive neuro-fuzzy inference system;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a sliding mode control strategy based on PSO (particle swarm optimization) and ANFIS (adaptive neuro-fuzzy inference system) to realize the trajectory tracking control of a 3-DOF robot manipulator. Firstly, the desired trajectory of the system end effector is discretized and PSO is employed to get the discrete joint angles of the robot manipulator. Then ANFIS is applied to turn the discrete joint angles into continuous joint angles. Finally, sliding mode controllers based on continuous joint angles are designed to perform the trajectory tracking of the robot manipulator. Simulation results validate the effectiveness of the control strategy.

引用

页码：973 / 977

页数：5

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