Optimal Network Estimator for Large Scale Continuous-Time Systems
连续大系统的网络结构最优滤波器

The paper deals with the real-time state estimation problem of large scale systems. Based on matrix minimum principle, an optimal network estimator is proposed. The algorithms derived are proven to be optimal for large scale system state estimation subject to information flow constraints in processing net, and have flexibility in comparision with decentralized or hierarchical methods. Clearly, multicomputer systems can be available to carry out the scheme.