摘要
针对汽车系统的非线性和参数不确定性,设计了一种"前馈+反馈"自适应神经模糊控制器,通过ESP和AFS的协调控制来提高汽车操纵稳定性。ESP反馈控制器采用模糊控制策略,以横摆角速度和质心侧偏角为控制目标;AFS前馈控制器采用径向基神经网络控制,以反馈控制器的输出作为误差进行学习,从而实现自适应控制。仿真结果表明,上述控制策略是可行和有效的,能显著改善汽车在高速或湿滑路面上的操纵稳定性。
In order to solve the problems of nonlinearity and parameters uncertainty of vehicle system, an adap- tive neural-fuzzy controller with feedforward and feedback is designed, which improves the handling stability of vehicle by coordinated control of electronic stability program（ESP） and active front steering（AFS）. The feed- back controller with ESP uses fuzzy control strategy to control yaw rate and side slip angle, while the feed-for- ward controller with AFS adopts radial basis function（RBF） neural network with the output of feedback con- troller as the error for learning to achieve adaptive control. The results of simulation show that the control strat- egy is feasible and effective, and it can greatly improve handling stability of vehicle on high-way and slippery road,~
出处
《测控技术》
CSCD
2015年第6期63-66,共4页
Measurement & Control Technology
基金
上海市教育委员会科研基金资助项目(04EB12)
