Distributed moving horizon state estimation of two-time-scale nonlinear systems

In this paper, we focus on distributed moving horizon estimation (DMHE) for a class of two-time-scale nonlinear systems described in the framework of singularly perturbed systems. By taking advantage of the time-scale separation property, a two-time-scale system is first decomposed into a reduced-order fast system and a reduced-order slow system. The slow system is further decomposed into several interconnected slow subsystems. In the proposed distributed state estimation scheme, a local estimator is designed for each slow subsystem and for the reduced-order fast system. The slow subsystem estimators communicate with each other to exchange information and they are only required to send information to the fast system one-directionally. The fast system estimator does not send out any information. The local estimators are designed as observer-enhanced moving horizon estimators. Sufficient conditions on the convergence of the estimation error of the DMHE are derived. The application of the proposed DMHE to a chemical process example demonstrates its applicability and effectiveness.