Identification of an unmanned aerial vehicle pilot-operator dynamics model under stochastic conditions

Abstract

The article is devoted to investigation of the new rules for identifying the pilot and his remnants dynamics models in the conditions of work as a part of a multidimensional closed-loop control system for an unmanned aerial vehicle. The article subject is the analysis of existing methods for identifying the dynamics model of a multidimensional object (pilot) as a closed-loop system part. An additive mixture of a vector random useful signals and random noises is allowed at the object output. The research purpose is to substantiate the object (pilot) frequency characteristics and noises’ (remnants) spectral densities matrices determining rules. All signals are assumed to be centered stationary random processes. The research method is based on the use of the control systems statistical dynamics rules. The application of the rules is illustrated by an example in the Matlab programming environment.