Simultaneous input and state estimation for stochastic nonlinear systems with additive unknown inputs

This paper investigates simultaneous input and state estimation for a class of nonlinear stochastic systems. We propose a recursive filter to concurrently estimate system states and unknown inputs. We show that the estimation errors of the proposed filter are Practically Exponentially Stable in probability, and the estimation error covariance matrices are uniformly bounded. (C) 2019 Elsevier Ltd. All rights reserved.