Dipl.-Ing. Timo Kautzmann
Dipl.-Inform. Micaela Wünsche
Prof. Dr.-Ing. Marcus Geimer
Dr.-Ing. Sanaz Mostaghim
Prof. Dr. Hartmut Schmeck

LAND.TECHNIK AgEng 2011 Tagungsband, S. 275-280

Abstract

Recent developments in modern mobile machines like tractors introduce a large number of degrees of freedom for designers and engineers to optimize the system according to their individual goals. However, current machine management strategies generally use only a small part of the evolving potential, and the efficiency of machine operation is highly influenced by the individual skills of the operator. We present a novel approach to consider the mobile machinery as a whole and employ a holistic optimization to maximize efficiency. The optimized working point is the result of several on- and offline learning loops, which assign optimal actions to a set of possible situations. This is realized using an Observer/Controller-architecture.