Decentralized state estimation for a large-scale spatially interconnected system. (March 2018)

• Record Type: Journal Article
• Authors: Liu, Huabo; Yu, Haisheng
• Is Part Of: ISA transactions. Volume 74(2018)
• Page Start: 67
• Page End: 76
• Publication Date: 2018-03
• Subjects: State estimation -- Decentralized -- Networked system -- Large-scale system -- Kalman filter; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2018.01.007
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) 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. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Highlights: A decentralized state estimator for large-scale interconnected systems is proposed. The computations efficiently utilize the characteristic of system structure. Some steady-state properties of the decentralized state estimator are provided.