Improving The Safety Stability Of Algorithms For Recurrent State Estimation Based On The Methods Of Conditionally Gaussian Filtering.

Abstract

In the world, research is underway to create a universal approach to assessing the state of stochastic control objects, focused on solving problems of adaptive control of dynamic objects. In this regard, an important task is to improve and modify methods and algorithms for adaptive estimation of the state of stochastic control objects based on the methods of conditionally Gaussian filtering in conditions of various kinds of disturbances and noises. [1]

Currently, the Republic pays great attention to the areas of automation and control, including the creation of advanced control systems that provide energy and resource savings in the automation and management of various technological processes and industries. The Strategy for the Further Development of the Republic of Uzbekistan for 2017–2021 sets out the tasks "... to reduce the energy intensity and resource intensity of the economy, to widely introduce energy-saving technologies into production, and to increase labor productivity in the sectors of the economy." In this aspect, the creation of effective algorithms for adaptive estimation of the state of stochastic control objects based on the methods of conditionally Gaussian filtering, which contribute to improving the accuracy and quality indicators of control processes, is very important.