An Overview of Neural Network and Fuzzy Logic Applications to Earthmoving Machine Systems Control

Over the past decade there has been a resurgence of interest in applying “artificial” intelligence techniques to control and decision-making systems. This paper surveys the applications of two artificial intelligence techniques, viz., neural networks and fuzzy logic, to earthmoving machine systems control. Neural networks can be thought of as a class of computational models that represent nonlinear input-output mappings, while fuzzy logic aims to capture the knowledge of experts in the form of rules expressed in linguistic terms. The papers reviewed cover their application to machine control, engine control, transmission control, diagnostics and prognostics, operator modeling, and other related applications.