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Open AccessArticle

A Decentralized Framework for Parameter and State Estimation of Infiltration Processes

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Department of Chemical & Materials Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
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Mathematics 2020, 8(5), 681; https://doi.org/10.3390/math8050681
Received: 28 March 2020 / Revised: 21 April 2020 / Accepted: 21 April 2020 / Published: 1 May 2020
The Richards’ equation is widely used in the modeling soil water dynamics driven by the capillary and gravitational forces in the vadose zone. Its state and parameter estimation based on field soil moisture measurements is important and challenging for field applications of the Richards’ equation. In this work, we consider simultaneous state and parameter estimation of systems described by the three dimensional Richards’ equation with multiple types of soil. Based on a study on the interaction between subsystems, we propose to use decentralized estimation schemes to reduce the complexity of the estimation problem. Guidelines for subsystem decomposition are discussed and a decentralized estimation scheme developed in the framework of moving horizon state estimation is proposed. Extensive simulation results are presented to show the performance of the proposed decentralized approach. View Full-Text
Keywords: state estimation; parameter estimation; moving horizon estimation; Richards’ equation; agro-hydrological systems state estimation; parameter estimation; moving horizon estimation; Richards’ equation; agro-hydrological systems
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MDPI and ACS Style

Bo, S.; Liu, J. A Decentralized Framework for Parameter and State Estimation of Infiltration Processes. Mathematics 2020, 8, 681. https://doi.org/10.3390/math8050681

AMA Style

Bo S, Liu J. A Decentralized Framework for Parameter and State Estimation of Infiltration Processes. Mathematics. 2020; 8(5):681. https://doi.org/10.3390/math8050681

Chicago/Turabian Style

Bo, Song; Liu, Jinfeng. 2020. "A Decentralized Framework for Parameter and State Estimation of Infiltration Processes" Mathematics 8, no. 5: 681. https://doi.org/10.3390/math8050681

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