电子科技2026，Vol.39Issue(9)：19-25,7.DOI:10.16180/j.cnki.issn1007-7820.2026.09.003
基于神经网络的移动机器人动态面控制
A Dynamic Surface Control Based on Neural Network for Mobile Robots
摘要
Abstract
In view of the motion control problem of mobile robots with highly time-varying parameters and un-known disturbances,as well as the friction and coupling problems among some subsystems during their motion pro-cess,a novel DSC(Dynamic Surface Control)method based on nonlinear DOB(Disturbance Observer)and RBFNN(Radial Basis Function Neural Network)is proposed.Approximate nonlinear functions such as friction in system dy-namics through neural networks.Combining the disturbance observer to handle the uncertainty of the mobile ma-chine system model and the external unknown disturbance to reduce the uncertainty of the system,more precise and stable motion control can be achieved.The stability of the closed-loop system is verified by using Lyapunov's stabil-ity theorem to ensure the reliability of the control scheme.The proposed control scheme is simulated on the MAT-LAB/Simulink platform,verifying that the controller can effectively ensure the robustness and accuracy of the mo-bile robot system in tracking the expected trajectory under various interferences and parameter uncertainties.关键词
移动机器人/动态面控制/运动控制/扰动观测器/神经网络/轨迹跟踪/未知扰动/非线性函数Key words
mobile robots/dynamic surface control/motion control/disturbance observer/neural network/trajectory tracking/unknown disturbance/nonlinear function分类
信息技术与安全科学引用本文复制引用
薛浩然,鲁守银,杨钊懿,王荣业,陈洪健..基于神经网络的移动机器人动态面控制[J].电子科技,2026,39(9):19-25,7.基金项目
山东省自然科学基金(2019JZZY010435,ZR2022MF309)Natural Science Foundation of Shandong(2019JZZY010435,ZR2022MF309) （2019JZZY010435,ZR2022MF309）
