Nonlinear Set-Membership Estimation and Its Application to the Design of an Interacting Multiple Model Estimator

Abstract

In this paper, an interacting multiple model (IMM) nonlinear set-membership estimation (NSME) is investigated for nonlinear systems with unknown-but-bounded (UBB) noises. First, two different NSME approaches are developed based on whether the characteristics of different noises are employed. Based on the proposed NSME method, a novel IMM-NSME algorithm is developed, which can be utilized to deal with the state estimation of multiple nonlinear models. Furthermore, the interaction between estimators depends on the switching probabilities described by the probability transition matrix, where the corresponding model probabilities are updated according to the designed rules. Then, the IMM-NSME algorithm is applied to address vehicle tracking, which is modeled as a combination of the constant velocity (CV) model and constant turning rate and velocity (CTRV) model. Finally, numerical simulations are provided to illustrate the validity of the developed methods.