Open AccessANISOTROPIC REGULATOR OF DAMPING OF RANDOM VIBRATIONS OF THE MOBILE PLATFORM OF A BILAMENT VEHICLE APPARATUS
Author(s) -
А. С. Абуфанас,
А. А. Лобатый,
Ю. Ф. Яцына
Publication year - 2017
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2017-3-13-19
Subject(s) - operability , control theory (sociology) , norm (philosophy) , kalman filter , engineering , probabilistic logic , computer science , control engineering , control (management) , artificial intelligence , law , political science , reliability engineering
The problem of damping of random effects on a mobile platform with a system for monitoring the earth’s surface installed on an unmanned aerial vehicle is considered. As an external influence, we consider the random turbulence of the atmosphere, described with the aid of a shaping filter, to which white noise enters. Monitoring system with a mobile platform is considered as a control system, the criterion of optimality of which is proposed to use the criterion of quality of the stochastic norm of the system, which quantitatively characterizes the sensitivity of the output of the system to random input disturbances whose probabilistic distribution is not known accurately. This leads to a special variant of the stochastic norm-the anisotropic norm. A technique for constructing a robust phase control system using an anisotropic regulator is considered. The coefficients of the optimal regulator are obtained by mathematical modeling. As an example for evaluating the operability of the proposed algorithm, one of the control channels of the mobile platform, defined by a discrete mathematical model of the second order, is considered. Qualitative illustrations of the operability of the proposed algorithm and quantitative characteristics of the change in output signals are presented. The use of anisotropic regulators in damping systems of random effects is promising, since it allows to reduce the influence on the quality of the system operation of uncertainties caused by the differences between the chosen mathematical model and the real optimized system.