摘要
在分析叉车结构和侧翻机理的基础上,设计了一种防侧倾液压油缸作为防侧翻控制的执行机构,以提供侧向支撑力;提出了一种基于T-S模糊神经网络的防侧翻分层控制方法,将叉车防侧翻进行分层控制:上层采用T-S模糊神经网络对叉车的实时运动状态进行判断,并作为下层控制的依据;中层控制层依据运动状态的划分分别选取对应的策略;下层执行层利用不同策略下执行机构的动作形式来控制模型的输出。仿真与实车试验结果表明,所提方法能够在叉车处于紧急工况下对安全域进行划分,以实现提高叉车安全性的目的。
Based on the analysis of forklift structures and rollover mechanism, an anti-roll hydraulic cylinder was designed as the actuator for anti-rollover control to provide lateral support forces. An anti-rollover hierarchical control method was proposed based on T-S fuzzy neural network. The forklift anti-rollover was controlled hierarchically: the T-S fuzzy neural network was used by the upper identification layer to judge the real-time motion states of the forklifts and as the basis of the lower layer control, the middle control layer selected the corresponding strategies according to the divisions of the motion states,the lower execution layer controlled the outputs of the model by the action forms of the actuators under different strategies. The simulation and real vehicle test results show that the proposed method may divide the safety domains of the forklifts under the emergency conditions and achieve the purpose of improving the safety of the forklifts.
作者
夏光
张洋
唐希雯
谢海
杨猛
高军
XIA Guang;ZHANG Yang;TANG Xiwen;XIE Hai;YANG Meng;GAO Jun(Automotive Research Institute,Hefei University of Technology,Hefei,230009;School of Radar Confrontation,National University of Defense Technology,Hefei,230037;School of Automotive and Traffic Engineering,Hefei University of Technology,Hefei,230009)
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2019年第17期2066-2075,共10页
China Mechanical Engineering
基金
国家自然科学基金资助项目(51875151)
关键词
平衡重式叉车
T-S模糊神经网络
防侧翻
分层控制
counterbalanced forklift
T-S fuzzy neural network
anti-rollover
hierarchical control
