欠驱动船舶自适应神经网络有限时间跟踪控制

doi:10.6040/j.issn.1672-3961.0.2021.496

摘要/Abstract

摘要： 针对受动态不确定性和外界未知干扰影响下欠驱动水面船舶的轨迹跟踪控制问题,设计一种有限时间轨迹跟踪控制方案。采用神经网络重构船舶的动态不确定性,通过引入最小学习参数降低计算复杂度,设计自适应律逼近由不确定项和外界干扰组合而成的复合扰动的上界,并基于此设计一种基于最小学习参数的欠驱动船舶自适应神经网络有限时间轨迹跟踪控制方案。通过严格的理论分析后得出,该有限时间轨迹跟踪控制方案能够使闭环系统的所有信号都趋于有界,欠驱动船舶的位姿误差和速度误差都在有限时间内收敛到一个集合。仿真和比较验证了本研究所提出的有限时间控制方案的有效性。本研究中的有限时间控制方案不仅提高了船舶的瞬态性能和稳态性能,且控制器结构简单,更容易应用在工程中。

关键词: 欠驱动水面船舶, 自适应神经网络, 轨迹跟踪, 有限时间, 最小学习参数

中图分类号:

U664.82

孟祥飞,张强,胡宴才,张燕,杨仁明. 欠驱动船舶自适应神经网络有限时间跟踪控制[J]. 山东大学学报 (工学版), 2022, 52(4): 214-226.

MENG Xiangfei, ZHANG Qiang, HU Yancai, ZHANG Yan, YANG Renming. Adaptive neural finite-time tracking control of underactuated marine surface vessel[J]. Journal of Shandong University(Engineering Science), 2022, 52(4): 214-226.

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