首页|水产养殖车间运输无人车延迟特性的路径跟踪控制

水产养殖车间运输无人车延迟特性的路径跟踪控制

扫码查看
为了提高水产养殖运输无人车在运送水产品过程中的路径跟踪准确性,本研究提出了一种考虑延迟特性的高精度路径跟踪控制方法。首先,对养殖车间内的无人车进行动力学分析,搭建了无人车动力学模型;其次,将通信延迟和执行器延迟表述为纯滞后模块和一阶惯性延迟模型,构建出延迟动力学模型;通过模型预测控制(MPC)算法,设计了适用于智能化养殖车间场景的控制器;通过MATLAB/Simulink和CarSim搭建仿真平台,并基于真实运输无人车和车间布局进行验证。结果显示,本实验方法相较于不考虑延迟的MPC控制器、仅考虑执行器延迟的MPC控制器、考虑延迟的LQR控制器,横向误差和航向角误差分别降低 96%和 95%以上、15%和 34%以上、5%和 28%以上。研究表明,本实验方法面对延迟问题时具有较好的路径跟踪性能。本研究解决了水产养殖运输无人车存在的延迟问题,路径跟踪精度得到提升,保证了养殖车间内无人车运输的准确性和安全性。
Path tracking control for aquaculture workshop transport unmanned vehicles considering delay characteristics
A high-precision path tracking control method considering delay characteristics was proposed to improve the path tracking accuracy of aquaculture transport unmanned vehicle in the process of transporting aquatic products.Firstly,the dynamics of the unmanned vehicle in the breeding workshop was analyzed.The dynamics model of the unmanned vehicle was built.Secondly,the communication delay and actuator delay were expressed as pure delay module and first order inertia delay model.The delay dynamic model was constructed.Through the model predictive control algorithm,the controller suitable for the intelligent breeding workshop scene was designed.The simulation platform was built by MATLAB/Simulink and CarSim,and verified based on the real transport unmanned vehicle and workshop layout.The results showed that compared with MPC controller without delay,MPC controller only considering actuator delay and LQR controller considering delay,the lateral error and course Angle error of the proposed method were reduced by 96%and 95%,15%and 34%,5%and 28%,respectively.The results showed that the proposed method performed better in path tracking when facing the delay problem.This study solves the delay problem of unmanned vehicles in aquaculture transportation,improves the path tracking accuracy,and ensures the accuracy and safety of unmanned vehicle transportation in aquaculture workshops.

driverless caraquaculture transportationintelligent farmingsteering delaymodel predictive control

曹守启、隋国庆、周国峰

展开 >

上海海洋大学工程学院,上海 201306

无人车 水产养殖运输 智慧养殖 转向延迟 模型预测控制

2024

水产学报
中国水产学会

水产学报

CSTPCD北大核心
影响因子:1.148
ISSN:1000-0615
年,卷(期):2024.48(12)