An RBFNN‐based constraint control algorithm for electric vehicle AFS + DYC system with state delays and uncertain parameters
Yu Zhou,
Youguo He,
Yingfeng Cai
et al.
Abstract:A novel multi‐input multi‐output adaptive control strategy applied to the combined active front steering (AFS) and direct yaw moment control (DYC) system is proposed in this paper. Studies have been conducted to show the potential for electric vehicles to be affected by time delay, which may appear in states. Aiming to address the state delay, radial basis function neural network (RBFNN) and Lyapunov‐Krakovskii functional‐based AFS and DYC controllers are constructed, which also can process the parameter uncer… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.