Adaptive Filter for Inertial Systems

The stochastic model of the disturbances handled by Kalman filters and the necessity of accurate identification of the dynamic model of the controlled system or process bring about a significant limitation of use of Kalman filters in practice. The paper presents filter designed for inertial systems whose models and control signals are not well known or are beyond description. The assumptions leading to a significant simplification of Kalman algorithm are described. On this basis, the algorithm with an experimentally matched parameter for the filter properties modification is introduced. An example of effective adaptive filtration is presented also.