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Bio-inspired robust control of a robot arm-and-hand system based on human viscoelastic properties

机译:基于人体粘弹性特性的机器人手臂系统的生物启发鲁棒控制

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摘要

A bio-inspired scheme based on the human multi-joint arm (HMJA) viscoelastic properties is proposed to design a robust controller for the complex robot arm-and-hand system (RAHS) using the operator -based robust right coprime factorization (RRCF) approach. The RAHS mainly consists of two components, a robot arm and a micro-hand with three fingers. The fingers are made up of miniature pneumatic curling soft (MPCS) actuators, and are located in the endpoint of the robot arm. The aim is for a human to intuitively control the robot arm to perform a task under unknown environments from a remote location. We identify the main limitations of standard interaction control schemes in obtaining the learned information pairs, then propose a new control approach that is inspired by the biological model of HMJA viscoelasticity in voluntary movements. To achieve the precise position of the robot arm and obtain the desired force using the micro -hand for coping with the external environment or task involved, we propose a two-loop feedback control architecture using the operator based RRCF approach. The bio-inspired inner-loop controller is designed based on HMJA viscoelastic properties to control the angular position of the robot arm. The outer-loop controller is designed to control the fingers force by considering the stable inner-loop as a right factorization. The robust tracking conditions and the realization of the proposed control system are also discussed. Finally, the effectiveness of the proposed control system is also verified by simulation results based on experimental data. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:提出了一种基于人体多关节手臂(HMJA)粘弹特性的生物启发方案,以使用基于操作员的鲁棒右互质分解(RRCF)设计复杂机器人手臂和手系统(RAHS)的鲁棒控制器。方法。 RAHS主要由两个部分组成,一个机械臂和一个带三个手指的微型手。手指由微型气动卷曲软(MPCS)致动器组成,位于机械臂的端点。目的是使人类直观地控制机器人手臂,以在未知环境下从远程位置执行任务。我们确定标准交互控制方案在获取学习的信息对中的主要局限性,然后提出一种新的控制方法,该方法受HMJA粘弹性在自愿运动中的生物学模型的启发。为了实现机器人手臂的精确位置并使用微型手来获得所需的力来应对所涉及的外部环境或任务,我们提出了一种基于操作员的RRCF方法的两环反馈控制架构。基于HMJA粘弹特性设计了受生物启发的内环控制器,以控制机器人手臂的角位置。外环控制器设计为通过将稳定的内环视为正确的因式分解来控制手指的力。还讨论了鲁棒跟踪条件和所提出的控制系统的实现。最后,基于实验数据的仿真结果也验证了所提出控制系统的有效性。 (C)2017富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2017年第4期|1759-1783|共25页
  • 作者单位

    Zhongyuan Univ Technol, Sch Elect & Informat Engn, Zhengzhou 450007, Peoples R China|Bournemouth Univ, Fac Sci & Technol, Bournemouth BH12 5BB, Dorset, England;

    Bournemouth Univ, Fac Sci & Technol, Bournemouth BH12 5BB, Dorset, England;

    Bournemouth Univ, Fac Management, Bournemouth BH12 5BB, Dorset, England;

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  • 入库时间 2022-08-18 02:57:43

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