用于机器人操纵器轨迹跟踪的顺应式可变导纳自适应固定时间滑动模式控制

IF 1.9 4区 计算机科学 Q3 ROBOTICS
Robotica Pub Date : 2024-05-02 DOI:10.1017/s0263574724000468
Hang Gao, Chao Ma, Xiaodong Zhang, Cheng Zhou
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引用次数: 0

摘要

本文提出了一种用于机器人操纵器轨迹跟踪的顺变导纳自适应固定时间滑模控制(SMC)算法。具体来说,将顺应式可变导纳算法和自适应固定时间 SMC 算法相结合,构建了一个双环控制结构。在外环中,开发了可变导纳算法,在碰撞过程中调整导纳参数,使碰撞时间最小化,从而使机器人具有顺应性,减少刚性碰撞的影响。然后,利用 Lyapunov 理论和定时稳定性理论,提出了一种新的非奇异滑模流形,并在内环中提出了一种自适应定时 SMC 算法。更确切地说,这种方法能实现快速收敛、更高的稳态跟踪精度以及与系统初始状态无关的稳定时间。因此,通过大量的模拟和实验结果,证明了所提算法的有效性和性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compliant variable admittance adaptive fixed-time sliding mode control for trajectory tracking of robotic manipulators
This paper presents a compliant variable admittance adaptive fixed-time sliding mode control (SMC) algorithm for trajectory tracking of robotic manipulators. Specifically, a compliant variable admittance algorithm and an adaptive fixed-time SMC algorithm are combined to construct a double-loop control structure. In the outer loop, the variable admittance algorithm is developed to adjust admittance parameters during a collision to minimize the collision time, which gives the robot compliance property and reduce the rigid collision influence. Then, by employing the Lyapunov theory and the fixed-time stability theory, a new nonsingular sliding mode manifold is proposed and an adaptive fixed-time SMC algorithm is presented in the inner loop. More precisely, this approach enables rapid convergence, enhanced steady-state tracking precision, and a settling time that is independent of system initial states. As a result, the effectiveness and improved performance of the proposed algorithm are demonstrated through extensive simulations and experimental results.
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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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