Applying fuzzy logic to the Kalman filter divergence problem

This paper explores the use of fuzzy logic in detecting and correcting the divergence of the Kalman filter. A fuzzy exponential-weighting algorithm is used to provide the corrective actions necessary to contain the divergence problem. Such actions are driven by the status of the innovations sequence. The soundness of the fuzzy central algorithm is demonstrated through computer simulations which are shown to comply with theoretical results