Probability-Guaranteed Envelope-Constrained Filtering for Nonlinear Systems Subject to Measurement Outliers

This article deals with the recursive filtering problem for nonlinear time-varying stochastic systems subject to possible measurement outliers. In order mitigate effects from abnormal measurements, we construct a filter saturation constraint imposed on innovations where level is adaptively determined according estimation errors. Two performance indices, namely, finite-horizon H ? specification and envelope-constraint criterion prescribed probability, are put forward describe transient characteristics of error dynamics over specified time interval. The purpose addressed design capable guaranteeing both index probability-guaranteed envelope-constraint. Sufficient conditions derived existence desired via certain convex optimization algorithms. Finally, an illustrative numerical example proposed demonstrate effectiveness developed algorithm.