首页|基于IGWO-MPC和NDO-ISMC级联算法的UUV轨迹跟踪控制器设计

基于IGWO-MPC和NDO-ISMC级联算法的UUV轨迹跟踪控制器设计

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
为了解决水下机器人(UUV)在受海流等复杂干扰力影响时的轨迹跟踪问题,设计了一种基于改进灰狼算法的模型预测控制(IGWO-MPC)和基于非线性干扰观测器的积分滑模控制(NDO-ISMC)级联的轨迹跟踪控制器.基于MPC方法设计了运动学控制器,提出利用在GWO算法中引入非线性收敛因子,基于个体经验和权重更新灰狼位置,以及反向学习策略所设计出的IGWO算法,来优化MPC的滚动优化求解过程,使机器人以期望的最优速度对给定位姿进行跟踪.基于IGWO-MPC运动学控制器得到的期望速度指令,设计了NDO-ISMC动力学控制器,该控制器利用NDO对干扰力进行估计,并对ISMC动力学输出控制律进行补偿以抑制扰动对跟踪精度的影响,同时输出扰动条件下机器人能够稳定跟踪上期望速度的控制推力.最后,利用MATLAB进行三维空间环境仿真,验证文章提出的将IGWO-MPC与NDO-ISMC算法级联的轨迹跟踪控制器能够使UUV在复杂水下环境下实现精确且稳定的轨迹跟踪.
Design of Trajectory Tracking Controller for UUV Based on IGWO-MPC and NDO-ISMC Cascaded Algorithm
To solve the trajectory tracking problem of unmanned underwater vehicle(UUV)under complex disturbances such as ocean currents,a cascaded trajectory tracking controller combined an improved grey wolf optimizer-based model predictive control(IGWO-MPC)with a nonlinear disturbance observer-based integral sliding mode control(NDO-ISMC)is designed.A kinematic controller is designed based on the MPC algorithm.Meanwhile,to enable the vehicle to achieve tracking of a given posture at the desired optimal speed,the IGWO is used in the rolling optimizing process of the MPC,which is designed by introducing a nonlinear convergence factor,based on individual experience and weight to update grey wolf position and opposition-based learning strategy into the GWO algorithm.Based on the desired velocity command obtained by the IGWO-MPC kinematic controller,a dynamics controller based on NDO-ISMC is designed.In this dynamic controller,the NDO is used to estimate the disturbances and compensate the output of the ISMC to suppress the effect of external disturbance on tracking accuracy.Meanwhile,the control thrust will be output by NDO-ISMC controller,so that the vehicle can track desired velocity stably under perturbed conditions.The simulation of three-dimensional space environment is conducted using MATLAB,which proves the trajectory tracking controller based on IGWO-MPC and NDO-ISMC cascaded algorithm proposed in the paper can enable the UUV to accomplish accurate and stable tracking controlin complex underwater environment.

unmanned underwater vehicletrajectory trackingmodel predictive controlgrey wolf optimizernonlinear disturbance observerintegral sliding mode control

覃国样、陈琦、张进

展开 >

上海海事大学物流工程学院,上海 201306

上海理工大学机械工程学院,上海 200093

中国科学院沈阳自动化研究所机器人学国家重点实验室,沈阳 110016

水下机器人 轨迹跟踪 模型预测控制 灰狼算法 非线性干扰观测器 积分滑模控制

国家自然科学基金资助项目国家自然科学基金资助项目上海市科技创新行动计划资助项目

519755655212781320dz1206700

2024

10.13788/j.cnki.cbgc.2024.02.01

船舶工程
中国造船工程学会

船舶工程

CSTPCD北大核心
影响因子：0.406
ISSN：1000-6982
年,卷(期)：2024.46(2)
  • 31