摘要
针对半主动悬架控制中的两个重要问题——系统模型的建立和控制策略的确定进行了深入的研究,建立了汽车的多体动力学方程,提出了半主动悬架模糊神经网络控制方法,设计了控制系统,应用遗传算法优化了控制器的参数和结构,用基于变尺度的BFGS算法优化神经网络权值,在仿真研究的基础上进行了试验研究,结果表明提出的方法能明显改善悬架性能。
Two important problems in the control of semi-active suspension which are the establishing of system model and the determination of control strategy are studied. The multi-body dynamic equations of the automobiles are deduced. After the study of applying fuzzy neural network method to the suspension control, the controller is designed. The GA algorithm is used to optimize the parameters and structure of the controller, and the DFGS algorithm is used to optimize weights of the network. Based on the simulation, the experiment is carried out. Both the simulation and experimental results show that the model and control strategy put forward can improve the performance of suspension noticeably.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2004年第1期104-108,共5页
Journal of Mechanical Engineering
基金
国家自然科学基金(50275045)
安徽省自然科学基金(0043238)
江苏省汽车工程重点实验室基金(KJS01087)资助项目。
