路面の特性変化に対応可能なアクティブステアリングのための非線形ニューロ制御

概要

論文の詳細を見る
To develop a front steering control system, a nonlinear steering control law is necessary, since the dynamical characteristics of cars are nonlinear at the situation of large side slip angle and high yaw rate. The robustness to change of friction coefficient μ is required on the controller. In this study, an intelligent control of front steering wheel is presented. The controller consists of two neural network controllers for specific μ and an integrator under the Cubic Neural Network (CNN) architecture. The neural networks are designed with error backpropagation learning. By using the CNN architecture, the controller can adapt to various values of μ. The effectiveness and the feasibility of the present active steering method are demonstrated by numerical simulation of simple 7 DOF model and DADS full vehicle model.
2001-02-25