控制理论与应用2026，Vol.43Issue(2)：278-286,9.DOI:10.7641/CTA.2024.30790
移动机器人轨迹跟踪的参数估计与原对偶神经网络预测控制
Trajectory tracking of mobile robots based on parameter estimation and primal-dual neural network predictive control
摘要
Abstract
This work focuses on the problem of uncertain parameter estimation and trajectory tracking for wheeled mobile robots.A method for estimating uncertain model parameters of mobile robots based on the convolutional neural network(CNN)is studied,and a primal-dual neural network(PDNN)model predictive control(MPC)tracking control algorithm for mobile robots is proposed.For wheeled mobile robots,tire lateral stiffness is affected by load disturbance,unmodelled dynamics and load changes,which is difficult to measure in real time during actual driving.CNN estimator of lateral stiffness is designed to eliminate uncertainty during robot operation considering the constraint conditions of front wheel deviation and acceleration.This work studies the design of predictive control for mobile robots based on CNN parameter estimation and proposes a PDNN based algorithm with CNN parameter estimation for solving the predictive control problem of mobile robots.The stability of the proposed PDNN-MPC algorithm is proved.Finally,to verify the effectiveness of the controller,the proposed PDNN-MPC algorithm is validated.关键词
轮式移动机器人/轨迹跟踪/模型预测控制/原对偶神经网络/卷积神经网络Key words
mobile robots/trajectory tracking/model predictive control/primal-dual neural network/convolutional neural network引用本文复制引用
张浪文,王中旭,魏海翔,谢巍..移动机器人轨迹跟踪的参数估计与原对偶神经网络预测控制[J].控制理论与应用,2026,43(2):278-286,9.基金项目
国家自然科学基金项目(62473160),广东省基础与应用基础研究基金项目(2023A1515030119,2023A1515240070),清远市科技计划项目(2023DZX006)资助.Supported by the National Natural Science Foundation of China(62473160),the Guangdong Basic and Applied Basic Research Foundation(2023A-1515030119,2023A1515240070)and the Science and Technology Planning Project of Qingyuan(2023DZX006). （62473160）
