摘要
为了提升AGV(Automated Guided Vehicle)的自动纠偏能力和运行稳定性,提出一种采用自适应神经模糊纠偏系统的纠偏方法。首先,建立AGV的运动学模型和纠偏模型。其次,在ANFIS编辑器中设计自适应神经模糊控制器。最后,在Adams与Matlab/Simlink软件中分别建立实验所需的AGV模型和纠偏系统。利用Adams与Matlab/Simlink软件的交互性,进行联合仿真实验,将自适应神经模糊纠偏系统与传统控制纠偏系统的实验结果进行对比分析。实验结果表明:自适应神经模糊纠偏系统能够提高AGV的纠偏效率,相较于模糊控制纠偏系统和神经网络纠偏系统,纠偏效率分别提高了42.4%和20.8%,且AGV的运行稳定性也能满足要求。
In order to improve the automatic deviation correction ability and operational stability during correction of AGV(Auto⁃mated Guided Vehicle),an correction method using an adaptive neuro-fuzzy correction system is proposed.Firstly,the kinematics model and deviation correction model of AGV are established.Secondly,the adaptive neuro-fuzzy controller is designed in ANFIS editor.Finally,the AGV model required for the experiment and the deviation correction system are established in Adams and Mat⁃lab/Simlink software respectively.The co-simulation experiment was carried out by using the interaction of Adams and Matlab/Simlink software.The experimental results of adaptive neuro-fuzzy deviation correction system and traditional control deviation correction system are compared and analyzed.The experiment results show that the adaptive neuro-fuzzy deviation correction sys⁃tem can improve the deviation correction efficiency of AGV.Compared with the fuzzy control deviation correction system and neuro deviation correction system,the deviation correction efficiency is improved by 42.4%and 20.8%respectively.And in the process of correction,the operational stability of AGV can also meet the requirements.
作者
袁斌
邵帅
李晨
祁景涛
YUAN Bin;SHAO Shuai;LI Chen;QI Jingtao(School of Mechanical and Energy Engineering Zhejiang University of Science and Technology,Zhejiang Hangzhou 310023,China)
出处
《机械设计与制造》
北大核心
2025年第1期335-339,共5页
Machinery Design & Manufacture
基金
基于多模态视觉检测技术的医疗大输液质量安全检测系统的研制—浙江省自然科学基金(LGF20F050002)。
