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Trajectory planning and tracking control for 6‐DOF Stanford manipulator based on adaptive sliding mode multi‐stage switching control
Author(s) -
Hu Qingxi,
Zhang Dianfeng,
Wu Zhaojing
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5628
Subject(s) - control theory (sociology) , trajectory , backstepping , grasp , computer science , sliding mode control , controller (irrigation) , kinematics , position (finance) , robotic arm , control engineering , tracking (education) , inverse kinematics , robot , engineering , adaptive control , control (management) , nonlinear system , artificial intelligence , psychology , pedagogy , physics , finance , astronomy , quantum mechanics , classical mechanics , agronomy , economics , biology , programming language
This article intends to investigate the trajectory planning and tracking control for six‐degrees‐of‐freedom (6‐DOF) Stanford manipulator consisting of 3‐DOF mechanical arm and 3‐DOF spherical wrist. By using Denavit–Hartenberg (DH) method, the Euler–Lagrange equations of motion of mechanical arm subsystem and spherical wrist subsystem are established, respectively. A new version of backstepping‐based adaptive sliding mode controller is proposed for trajectory tracking of each subsystem. In order to grasp an object from one point to another, a special smooth continuous trajectory is planned by inverse kinematics analysis which transforms the position of the end‐effector in the task space to the joint position in the joint space. After that, a multi‐stage switching control strategy is proposed to achieve trajectory tracking control. Simulation results are provided to demonstrate the performance of the proposed control strategy.