Publication

Nonlinear moving horizon estimator for online estimation of the density and viscosity of a mineral slurry

Journal Article (2018)

Journal

Industrial and Engineering Chemistry Research

Doc link

http://dx.doi.org/10.1021/acs.iecr.7b04393

File

Download the digital copy of the doc pdf document

Authors

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, 2018, to appear.