NEURAL NETWORK AND FUZZY LOGIC APPLICATIONS TO VEHICLE SYSTEMS: LITERATURE SURVEY

Abstract

Recent developments in the application of the artificial neural networks (NN) and fuzzy logic (FL) have attracted the attention of many researchers in the area of vehicle dynamics and control. Neural networks are able to emulate the solution of different classes of nonlinear algebraic equations and differential transfer functions. Fuzzy logic interface systems can map those functions that have no equivalent mathematical model or whose mathematical models are very complicated. A large number of studies have been published on the application of neural networks and fuzzy logic interface systems to vehicle dynamics and control. In this paper, an extensive literature survey of more than forty papers and reports, published during the last five years, has been conducted. Reviewed papers cover different subjects including: vehicle motion control, driver modelling, tyre modelling, braking control, suspension control, steering system, transmission control, and engine control. This literature review is part of an ongoing research project related to the application of neural networks and fuzzy logic to vehicle dynamics and control.