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Distributed simultaneous state and parameter estimation of nonlinear systems
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In this paper, we consider distributed simultaneous state and parameter estimation for a class of nonlinear systems, for which the augmented model comprising both the states and the parameters is only partially observable. Specifically, we first illustrate how the sensitivity analysis (SA) can select variables for simultaneous state and parameter estimation. Then, a community structure detection (CSD) based process decomposition method is proposed for dividing the entire system into interconnected subsystems as the basis of distributed estimation. Next, we develop local moving horizon estimators based on the configured subsystem models, and the local estimators communicate with each other to exchange their estimates. Finally, an SA and CSD based distributed moving horizon estimation (DMHE) mechanism is proposed. The effectiveness of the proposed approach is illustrated using a chemical process consisting of four connected reactors.
Subsystem decompositionSensitivity analysisCommunity structure detectionDistributed estimationNonlinear process
Siyu Liu、Xunyuan Yin、Jianbang Liu
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School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore 637459, Singapore
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
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