Modelling and vibration control for deep-sea robot lifting system with time variable length and nonlinear disturbance observer

Modelling and vibration control for deep-sea robot lifting system with time variable length and nonlinear disturbance observer
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DOI:
10.1016/j.oceaneng.2022.110558
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发表时间:
2022-02
期刊:
影响因子:
5
通讯作者:
Naige Wang;Xiaoqin Xiang;Yongying Jiang;Rong-Tai Yang
Naige Wang;Xiaoqin Xiang;Yongying Jiang;Rong-Tai Yang
中科院分区:
工程技术2区
文献类型:
--
作者:
Naige Wang;Xiaoqin Xiang;Yongying Jiang;Rong-Tai Yang

文献摘要

相似文献

在本文中,我们提出了一种数学模型,旨在消除具有时变长度和恶劣环境条件的深海机器人提升系统的振动。可变长度脐带缆被建模为具有附加集总质量的移动绳,理论上具有偏微分方程(PDE),并通过改进的假定模式方法(AMM)进行空间离散。控制方案考虑了深海机器人的三个特征,即非匹配不确定性、刚柔耦合和输入饱和。结合Lyapunov理论和LaSalle不变定理,提出了一种鲁棒自适应反馈控制来消除深海机器人的振动。此外,科学设计了非线性扰动观测器(NDO)来估计未知边界不确定性及其耦合,同时呈现整个控制系统的稳定性。进一步开发了非线性函数来解决执行器输入非线性的潜在问题。首先通过 ADAMS 仿真说明系统的动态建模,然后对不同情况进行更详细的分析,以证明当前方法的有效性。
In this paper, we propose a mathematical model meant to eliminate the vibration of deep-sea robot lifting system with time-variant length and harsh environmental conditions. The variable-length umbilical cable is modelled as a moving string with additional lumped-mass that has a partial differential equation (PDE) theoretically, spatially discretized by the modified assumed modes method (AMM). Three features of the deep-sea robots are considered in the control schema i.e. non-matched uncertainties, rigid-flexible couplings, and input saturation. By combining Lyapunov theory and LaSalle's invariance theorem, a robust adaptive feedback control is proposed to eliminate vibration of the deep-sea robot. In-addition, a nonlinear disturbance observer (NDO) is scientifically designed to estimate the unknown boundary uncertainties and their couplings, where the stability of whole control system is simultaneously presented. A nonlinear function is further developed to settle out the potential problem of input nonlinearities for the actuator. The dynamic modelling of the system is first illustrated by the ADAMS simulation and followed by more detailed analyses of different cases to demonstrate the effectiveness of the current method.