부산대학교 도서관

This article investigates the distributed nonlinear and linear Kalman filters for dynamical systems with state equality constraints via a sensor network, where each sensor estimates the system states by utilizing its own and neighbors' information. First, a constrained distributed extended Kalman filter is proposed, and its stability is proven under feasibility conditions. Then, this constrained distributed extended Kalman filter is relaxed to the linear form, obtaining more precise results under weaker conditions. Moreover, a local constraint fusion algorithm is proposed. Finally, the effectiveness of the proposed filters is demonstrated by two simulation examples.