Publication
Nonlinear moving horizon estimator for online estimation of the density and viscosity of a mineral slurry
Journal Article (2017)
Journal
Industrial and Engineering Chemistry Research
Pages
14592–14603
Volume
56
Number
49
Doc link
http://dx.doi.org/10.1021/acs.iecr.7b04393
File
Authors
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Diaz Castañeda, Jenny Lorena
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Ocampo Martínez, Carlos A.
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Alvarez Zapata, Hernán Darío
Abstract
This paper proposes a moving horizon estimator for nonlinear systems with unknown inputs, which do not comply with the model structures proposed in the literature for the design of nonlinear observers. The estimator is designed as an optimization problem over a moving horizon, constrained to process model equations and considering the unknown inputs as random inputs among their operating bounds. This proposal is applied to the transport of mineral slurries among process units, typically present in chemical and biological processes. There, to have the slurry properties as on-line measurements is vital to an efficient control of those processing units. The performance of proposed estimator is evaluated by simulation with data from a real processing plant, and its performance is compared with a linear estimator executing the same estimation task. Better results are obtained using the proposed estimator by considering the nonlinearities of the process.
Categories
nonlinear programming, optimisation.
Author keywords
Moving horizon estimation, optimization-based estimation, nonlinear systems, fluid transport, density and viscosity estimation
Scientific reference
J.L. Diaz, C. Ocampo-Martínez and H. Alvarez. Nonlinear moving horizon estimator for online estimation of the density and viscosity of a mineral slurry. Industrial and Engineering Chemistry Research, 56(49): 14592–14603, 2017.
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