Abstract
Recently, direct yaw moment control (DYC) using active brake has been applied on some vehicles. Its control law is determined from result of nonlinear simulation analysis. But, choosing significant inputs to DYC controller is difficult because of nonlinearity of tire-road force. The neural network (NN) can find control law of nonlinear system, but to understand the meaning is difficult because of its complex structure. In this paper, rule extraction from NN controller is presented. The NN controller is obtained by using nonlinear mathematical simulation of double lane change with genetic algorithm (GA). By addition forgetting genetic operator, the connection of NN are reduced and simplified. As a result, simple control law of DYC is achieved. The control law can be implemented by various means because of its simplicity. The DYC control law using side slip angle and time derivative of side slip angle is achieved. This control law has good performance and uses the same inputs as the DYC controller that was obtained by conventional analysis method. As a result, the effectiveness of rule extraction from NN is presented.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
