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Characteristic model-based control of robotic manipulators with dynamic uncertainties

参数不确知机械臂系统基于特征模型的控制方法研究

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摘要

创新点

本文研究了机械臂系统基于特征模型的输出反馈离散自适应控制。 基于特征模型的自适应控制方法仅需要对象的输入输出信息就能够设计形式简单的控制器, 对机械臂系统特征建模后得到的是一个多输入多输出的时变系统, 科氏力项的存在使得时变系统的参数界依赖于速度的界, 导致控制器的设计和闭环稳定性分析难度大大增加。 为解决上述难题, 本文给出了如下创新结果:

  1. 1)

    提出了包含状态信息的投影辨识算法, 解决了参数界依赖于速度的界引入的难点;

  2. 2)

    设计了基于离散滑模矢量的自适应控制算法, 使得运动学和动力学回路保持简单直观的级联结构;

  3. 3)

    利用特征模型理论和离散域稳定分析工具对闭环回路进行了稳定性分析, 在控制器参数和辨识算法投影界满足一定条件时, 得到了结点位置渐近稳定的结果, 推广了特征模型的理论框架, 为特征模型的稳定性分析提供了一种新的思路。

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Correspondence to Bin Meng.

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The authors declare that they have no conflict of interest.

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Wang, L., Meng, B. Characteristic model-based control of robotic manipulators with dynamic uncertainties. Sci. China Inf. Sci. 60, 079201 (2017). https://doi.org/10.1007/s11432-015-0356-5

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  • DOI: https://doi.org/10.1007/s11432-015-0356-5

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