基于固定时间积分滑模观测器的双闭环UUV轨迹跟踪控制
Dual Closed-Loop UUV Trajectory Tracking Control Based on Fixed-Time Integral Sliding Mode Observer
王元慧 1程基涛 1邵燕 2邵兴超1
作者信息
- 1. 哈尔滨工程大学智能科学与工程学院,哈尔滨 150001
- 2. 武汉第二船舶设计研究院,武汉 430000
- 折叠
摘要
针对水下无人航行器(UUV)轨迹跟踪控制问题,设计一种基于固定时间积分滑模观测器(FTISO)的双闭环运动控制策略.建立UUV运动数学模型,对运动学外环设计积分滑模控制器,使用非线性微分器获得外环虚拟控制律的导数,以保证航行器位置能够精确收敛.考虑动力学内环存在的模型不确定性和外部干扰难以测量等问题,采用FTISO实现对集总干扰快速估计,同时引入李雅普诺夫函数分析系统的稳定性.在仿真环境下对比基于FTISO的双闭环积分滑模控制与积分滑模控制、RBF网络自适应滑模控制的控制效果.仿真结果表明:基于FTISO的双闭环滑模控制对集总干扰有良好的补偿能力,可提高控制系统的性能及精度,可保证UUV在不同环境下均能实现轨迹跟踪.
Abstract
Aiming at the trajectory tracking control problem of an unmanned underwater vehicle(UUV),a dual-loop motion control strategy based on a fixed-time integral sliding mode observer(FTISO)is designed.Firstly,the mathematical model of UUV motion is established.An integral sliding mode controller is designed for the kinematic outer loop,and a nonlinear differentiator is utilized to obtain the derivative of the virtual control law in the outer loop,in order to ensure precise convergence of the UUV position.Secondly,considering the model uncertainties in the dynamic inner loop and the difficulty in measuring external disturbances,a FTISO is employed to achieve fast estimation of the total disturbances.The stability of the system is analyzed using Lyapunov function.In a simulation environment,the control performance of the dual closed-loop integral sliding mode control based on FTISO is compared with that of the integral sliding mode control and the RBF network-based adaptive sliding mode control.The simulation results demonstrate that the dual closed-loop sliding mode control based on FTISO has good compensation ability for total disturbances,the method improves the performance and accuracy of the control system,and ensures the UUV trajectory tracking in different environments.
关键词
水下无人航行器/轨迹跟踪控制/固定时间积分滑模观测器/双闭环积分滑模控制器Key words
unmanned underwater vehicle(UUV)/trajectory tracking control/fixed-time integral sliding mode observer/dual closed-loop integral sliding mode controller引用本文复制引用
基金项目
国家自然科学基金项目(51879049)
黑龙江省自然科学基金项目(LH2019E039)
出版年
2024
NETL
NSTL
万方数据