This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum me...

This paper investigates the multi-agent persistent monitoring problem via a novel distributed submodular receding horizon control approach. In order to approximate global performance, with definition of sub-modularity, original objective is divided into several local objectives in framework, and optimal trajectories each agent are obtained by taking account neighborhood information. Specificall...

Model-error control synthesis is a nonlinear robust control approach that uses an optimal solution to cancel the effects of modelling errors and external disturbances on a system. In this paper the optimal solution for a modified approximate receding-horizon problem is used to determine the model error in an aeroelastic system, which has several uncertain parameters, including a nonlinear sprin...