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Optimal sensor placement for agro‐hydrological systems
Author(s) -
Sahoo Soumya R.,
Yin Xunyuan,
Liu Jinfeng
Publication year - 2019
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.16795
Subject(s) - observability , discretization , computer science , linearization , mathematical optimization , nonlinear system , scale (ratio) , reduction (mathematics) , state space , work (physics) , control theory (sociology) , mathematics , engineering , control (management) , statistics , artificial intelligence , mathematical analysis , physics , mechanical engineering , geometry , quantum mechanics
The estimation of soil moisture is essential for developing advanced closed‐loop irrigation schemes. One associated problem is how to place the sensors appropriately in the soil to provide good measurements for state estimation. In this work, we address the problem of optimal sensor placement for state estimation of agro‐hydrological systems. A systematic approach is proposed to find the minimum number of sensors that ensures the observability of the entire system and then to find the best locations of the sensors in terms of degree of observability. The Richards equation that is used to describe the dynamics of the agro‐hydrological system is discretized into a large‐scale nonlinear state‐space model. In the proposed procedure, the key steps include order reduction of the large‐scale system model, exploration of the minimum number of sensors needed for state estimation and optimal placement of the sensors in the soil. Three different scenarios are considered and optimal sensor placement is addressed for all the scenarios using the proposed procedure. Simulation results show the effectiveness of the proposed procedure and methods.