Kalman filtering and control algorithms for systems with unknown disturbances and parameters using nonparametric technique

The paper deals with the Kalman filtering and control algorithms for a class of systems with uncertainty (unknown additive inputs). Such classes include object models with possible failures and also models of controlled processes with unknown disturbances and parameters. The designed algorithms are based on combining the Kalman filter and nonparametric estimator. Examples are given to illustrate the usefulness of the proposed approach.