Application of model and process features in set-valued dynamical system state estimation

Abstract

The article deals with the issue of set-valued dynamical system state estimation. The known algorithms of set-valued dynamical system state estimation are developed when the mathematical model of disturbances and noises is unknown but the sets of their possible values are available. The set-valued estimate is computed for all possible values of disturbances and noises. However, some additional information on the character of disturbances and noises can be available. Additional information about uncertain system parameters can be used to reduce computational complexity and to increase estimates accuracy.