Abstract
The internal and external interferences causing changes in the characteristics of automatic control systems of aircraft gas-turbine engines (ACS GTE) are analyzed. Solution of the adaptation problem and monitoring ACS GTE parameters’ is based on the application of identification methods. The purpose of this work is the development of multi-dimensional Kalman filter connected to the output of the built-in mathematical dynamic model of the gas-turbine engine to improve the parameters’ identification and to achieve high-quality automatic control. The possibility of using the Kalman filter for this class of dynamic processes was proved by statistical analysis of experimental statistics method, based on Slutsky criterion. The basic mathematics, which are underlying the algorithms of optimal multidimensional filtering, were considered. The approbation of the proposed algorithms was made by MatLab. The simulation results showed that the using of multi-dimensional matrix Kalman filters in ACS GTE model allows to achieve higher rates parameters’ identification accuracy than analogues used in current technology practice.
