具有输入饱和和执行器故障的自主水下航行器有限时间旋转矩阵跟踪控制

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Cheng Zhu, Bing Huang, Yumin Su, Yuxin Zheng, Shuai Zheng
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引用次数: 10

摘要

本文研究了存在输入饱和约束、执行器故障、未知动力学和外部干扰的自主水下航行器(AUV)有限时间全局轨迹跟踪控制问题。首先,我们用旋转矩阵代替经典的欧拉角或单位四元数来描述AUV的方向,使AUV的动力学可以全局表述,没有奇点和解卷现象。然后,引入光滑死区模型对执行器模型进行线性化,使自适应律适用于输入饱和和执行器故障的求解。考虑到模型动态获取的难度,以及基于旋转矩阵表示的复杂性,会给控制器的部署带来麻烦。利用最小学习参数技术来逼近水下航行器的动态非线性。在此基础上,提出了一种基于旋转矩阵的滑模控制方案。结果表明,在一定的稳定时间内,跟踪误差可以稳定在一个小的邻域内。最后,进行了几组数值实验,以评估所提出的控制方案的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finite‐time rotation‐matrix‐based tracking control for autonomous underwater vehicle with input saturation and actuator faults
This article tackles the finite‐time global trajectory tracking control problem of the autonomous underwater vehicle (AUV) in presence of input saturation constraints, actuator faults, unknown dynamics, and external disturbances. First, we describe the orientation of the AUV by rotation matrix instead of classical Euler angle or unit quaternion such that the AUV's dynamics could be globally formulated without singularity and unwinding phenomenon. After that, a smooth dead zone‐based model is introduced here to linearize the actuator model, leaving that the adaptive laws could be suitable for the solution of input saturation and actuator faults. Considering that the difficulty of model dynamic acquirement, together with the complicity of rotation‐matrix‐based representation, would trouble deployment of the controller. The minimum learning parameter technology is thereby utilized to approximated the dynamic nonlinearity of the AUV. On the basis of these, a rotation‐matrix‐based sliding mode control scheme is technically proposed. It is proved that the tracking errors can be stabilized to a small neighborhood of origin within a settling time. Finally, several set numerical experiments are conducted to assess the effectiveness and show the advantages of the proposed control scheme.
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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