A review on robust M-estimators for regression analysis
Regression analysis constitutes an important tool for investigating the effect of explanatory
variables on response variables. When outliers and bias errors are present, the weighted …
variables on response variables. When outliers and bias errors are present, the weighted …
Robust data reconciliation in chemical reactors
Robust data reconciliation is an effective technique designed to minimize gross errors
drawbacks over estimated process variables. This work presents a review focusing on …
drawbacks over estimated process variables. This work presents a review focusing on …
Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial polypropylene reactor
In a previous study, a nonlinear dynamic data reconciliation procedure (NDDR) based on
the particle swarm optimization (PSO) method was developed and validated in line and in …
the particle swarm optimization (PSO) method was developed and validated in line and in …
Numerical aspects of data reconciliation in industrial applications
Data reconciliation is a model-based technique that reduces measurement errors by making
use of redundancies in process data. It is largely applied in modern process industries …
use of redundancies in process data. It is largely applied in modern process industries …
Robust estimators for data reconciliation
CE Llanos, MC Sanchez… - Industrial & Engineering …, 2015 - ACS Publications
In this work, a comparative performance analysis of robust data reconciliation strategies is
presented. The study involves two procedures based on the biweight function and three …
presented. The study involves two procedures based on the biweight function and three …
Development of robust extended Kalman filter and moving window estimator for simultaneous state and parameter/disturbance estimation
Simultaneous occurrence of gross errors (outliers/biases/drifts) in the measured signals, and
drifting disturbances/parameter variations affecting the system dynamics can lead to biased …
drifting disturbances/parameter variations affecting the system dynamics can lead to biased …
Robust state estimation of feeding–blending systems in continuous pharmaceutical manufacturing
State estimation is a fundamental part of monitoring, control, and real-time optimization in
continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard …
continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard …
Vapor pressure and vapor-liquid equilibrium data for eugenol/caryophyllene binary system at low pressures by experimental and predictive methods
The main objective of this study was to determine the vapor-liquid equilibrium of the binary
mixture eugenol/caryophyllene at reduced pressures and to obtain pure compounds vapor …
mixture eugenol/caryophyllene at reduced pressures and to obtain pure compounds vapor …
Simultaneous model selection, robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation
ED Valdetaro, R Schirru - Annals of Nuclear Energy, 2011 - Elsevier
Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing
interest in Nuclear Power Plants and used in order to keep Mass and Energy balance into …
interest in Nuclear Power Plants and used in order to keep Mass and Energy balance into …
Robust data reconciliation of combustion variables in multi-fuel fired industrial boilers
T Korpela, O Suominen, Y Majanne… - Control Engineering …, 2016 - Elsevier
This paper introduces an application of simultaneous nonlinear data reconciliation and
gross error detection for power plants utilizing a complex but computationally light first …
gross error detection for power plants utilizing a complex but computationally light first …