摘要
在对可调阻尼减振器试验基础上,建立了半主动悬架非线性模型,并与线性模型进行了对比分析,采用间接学习的神经网络反馈控制方法,根据半主动悬架性能评价函数的要求直接调整神经网络的权值,收敛快。仿真试验表明,由该模型构建的半主动悬架控制规则易于实现,控制效果更为显著。
Based on the experiments of variable damper, the nonlinear model of semi-active suspension is established and compared with the linear one. The convergence speed is high by adapting the power value of neural network adopted indirect study method of neural network control according to the demand of the performance value function of semi-active suspension. The result of simulation indicates that the semi-active suspension control law configured by the model is easy to realize and the control effect is remarkable.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2005年第5期137-141,共5页
Journal of Mechanical Engineering
基金
国家自然科学基金(50275064)江苏省自然科学基金(BK2001199)江苏省高新技术(BG2004025)资助项目。
关键词
半主动悬架
可调减振器
控制
Semi-active suspension Variable damper Control
