What is it about?
A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix.
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Why is it important?
An optimization problem is constructed for the computations of improved subsystem parameter matrices used for a decentralized state estimator of the spatially interconnected systems constituted by many subsystems with arbitrary connection relations. Direct utilization of the computation approaches based on the rearranged lumped systems may usually encounter implementation prohibitions. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix.The obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system.
Perspectives
This paper may be interesting to the readers whose research interests are state estimation, decentralized control and estimation, networked system, large scale system and distributed control etc.
Huabo Liu
Qingdao University
Read the Original
This page is a summary of: Robust state estimation for wireless sensor networks with data-driven communication, International Journal of Robust and Nonlinear Control, April 2017, Wiley,
DOI: 10.1002/rnc.3819.
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