Automatic Optimization of Motion Drive Algorithms using OMCT

Abstract

The standard approach to Motion Drive Algorithm (MDA) optimization is using subjective pilot feedback to evaluate the effect of changes to the MDA parameter setting. This is an expensive process because it requires the use of the Flight Simulation Training Device (FSTD), an evaluation pilot and an MDA tuning expert. Furthermore, the resulting MDA parameter set will differ from pilot to pilot. Therefore, an automatic MDA optimization method has been developed that can be executed on any desktop computer. The optimization method is based on ICAO’s Objective Motion Cueing Test (OMCT) and associated fidelity criteria, which are currently being developed under the guidance of the Royal Aeronautical Society. OMCT allows an MDA parameter setting to be objectively scored based on MDA performance criteria in the frequency domain. Providing a collection of different parameter sets, each with their individual scores, the Nelder-Mead simplex method is used to search heuristically for the optimal parameter set for the MDA. This paper discusses the developed automatic optimization method and its optimization results for two MDAs. The MDAs used in this study are an FSTD industry standard and the Dutch National Aerospace Laboratory’s (NLR) MDA of their GRACE full flight research simulator. This new method allows an MDA to be optimized offline by engineers with limited MDA optimization knowledge and experience.