Model-based control of the flying helicopter simulator: evaluating and optimizing the feedback controller

Abstract

The numerical evaluation and optimization of the feedback controller parameters of the model-based control implemented in the flying helicopter simulator is subject of this paper. The German Aerospace Center operates this helicopter as a flying testbed for numerous applications, e.g., pilot assistance and in-flight simulation. Initially, the elements of the model-based control are pre- sented. A genetic algorithm and the Nelder–Mead simplex method used for optimization are described. Two simple objective functions to rate parameter sets in the time domain are presented, and a Simulink model of the helicopter dynamics and the controller structure are used to find optimized sets. The first function, called ‘‘Delta Rating’’, consists of a normalized integral of the absolute error between commanded and measured states. The second function incorporates the Delta Rating, but is enhanced by a penalty on overshoots. The controllers found are further evaluated using a frequency domain approach consisting of a weighted sum of the differences in amplitude and phase, also considering the coherence at the corresponding fre- quency. Apart from the Simulink model, a ground-based simulator is used to evaluate the standard and the optimized controllers.