To the problem of measurement errors estimation in control systems with incomplete information

The article deals with the problem of increasing the accuracy of the state estimation of linear dynamical systems under conditions of incomplete information. This problem is linked to the feature of guaranteed estimation methods, which is that the allowable sets of values of disturbances acting on the system and measurement errors in the information-measuring channel can be only rough upper bound on a short observation interval. In particular, for a single short measurement implementation, the probability of the realization of disturbances and measurement errors is worst-case less than one. The approach to adaptive algorithm development of guaranteed estimation is proposed. The approach is based on processing the innovation sequence values of the Kalman filter. The Kalman filter implementation is performed for measurement data preprocessing. The innovation sequence is considered as a time series for processing of which statistical and guaranteed estimation methods are used. The results of processing the innovation sequence values are used to construct bounded estimates of the measurement errors used in the equations of the guaranteed estimation algorithm. With this approach an informational definition of unknown measurements errors is carried out. The main feature of the problem studied in this article is a small number of available measurements the results of which are used to find the best estimate of the state vector. Therefore, the implementation of measurements is considered as a short time-series. To reduce the computational cost of implementing the guaranteed real time estimation algorithm, methods for decomposition of the estimation problem are proposed. The effectiveness of the proposed approach is demonstrated by the example of a model describing the spacecraft attitude motion. The results of simulation and a comparative analysis of the accuracy of the obtained estimates of the state vector are presented. The results of simulation and a comparative analysis of the accuracy of the obtained state estimates are given.