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基于双羟乙哌嗪-洛匹那韦的具有多种不确定性的欠驱动自主水下航行器鲁棒三维路径跟踪控制

DO-LPV-based robust 3D path following control of underactuated autonomous underwater vehicle with multiple uncertainties.

作者信息

Zhang Yuwei, Wang Xingjian, Wang Shaoping, Miao Jianming

机构信息

School of Automation Science and Electrical Engineering, Beihang University, 100191 Beijing, China.

School of Automation Science and Electrical Engineering, Beihang University, 100191 Beijing, China; Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, 100191 Beijing, China.

出版信息

ISA Trans. 2020 Jun;101:189-203. doi: 10.1016/j.isatra.2020.01.017. Epub 2020 Jan 16.

Abstract

This study investigates a path following problem of underactuated autonomous underwater vehicle under multiple uncertainties in three-dimensional space. The uncertainties are partly induced by hydrodynamic coefficient uncertainty, ocean currents and unmodeled hydrodynamics, namely dynamic uncertainties. In addition, velocities are assumed to be measured with bounded noise, which is called velocity measurement uncertainties. To address this issue, a compound robust path following control strategy is developed. At the kinematic level, an improved kinematic controller is developed by utilizing disturbance observer to recover the unknown time-varying attack and side-slip angular velocity. At the dynamic level, a novel dynamic tracking model is firstly established via linear parameter varying (LPV) technique, by which multiple uncertainties are expressed in a comprehensive way. Subsequently, a robust LPV controller is employed to track desired velocities generated by kinematic controller, which has less dependence on accurate model and exact velocity measurement. Finally, rigorous stability analysis proves the uniform and ultimate boundedness of path following errors. The comparative numerical results also substantiate the efficacy and superiority of designed method.

摘要

本研究探讨了三维空间中存在多种不确定性的欠驱动自主水下航行器的路径跟踪问题。这些不确定性部分由水动力系数不确定性、洋流和未建模的水动力引起,即动态不确定性。此外,假设速度测量存在有界噪声,这被称为速度测量不确定性。为解决此问题,开发了一种复合鲁棒路径跟踪控制策略。在运动学层面,通过利用干扰观测器来恢复未知的时变攻角和侧滑角速度,开发了一种改进的运动学控制器。在动力学层面,首先通过线性参数变化(LPV)技术建立了一个新颖的动态跟踪模型,通过该模型可以综合表达多种不确定性。随后,采用鲁棒LPV控制器来跟踪运动学控制器生成的期望速度,该控制器对精确模型和精确速度测量的依赖性较小。最后,严格的稳定性分析证明了路径跟踪误差的一致最终有界性。比较数值结果也证实了所设计方法的有效性和优越性。

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