A REVISION OF THE MOST FREQUENT METHODS FOR STATE ESTIMATION IN CHEMICAL PROCESSES

This paper shows a literature review of some proposed methods for state estimation in chemical processes industry. The revision is made for estimators of fixed sampling time. The analysis is done considering the types of estimators, the types of models used by the estimators, the reported applications for those estimators, the advantages and the limitations of estimators use. Finally, a real problem of state estimation in an industrial process is exposed.

[1]  Masoud Soroush.  State and parameter estimations and their applications in process control , 1998 .

[2]  Rajagopalan Srinivasan,et al.  Multi-linear model-based fault detection during process transitions , 2003 .

[3]  José Luis Figueroa,et al.  A high gain nonlinear observer: application to the control of an unstable nonlinear process , 2004, Comput. Chem. Eng..

[4]  J. A. Wilson,et al.  A generalised approach to process state estimation using hybrid artificial neural network/mechanistic models , 1997 .

[5]  Denis Dochain,et al.  State and parameter estimation in chemical and biochemical processes: a tutorial , 2003 .

[6]  Stanley M. Walas,et al.  Chemical Process Equipment : Selection and Design , 1988 .

[7]  Moses N. Bogere,et al.  A rigorous description of gas-solid fluidized beds , 1996 .

[8]  F. Chejne,et al.  An experimental study on gasification of Colombian coal in fluidised bed , 2003 .

[9]  Dan Simon,et al.  A comparison of filtering approaches for aircraft engine health estimation , 2008 .

[10]  D. Himmelblau,et al.  Optimization of Chemical Processes , 1987 .

[11]  Chonghun Han,et al.  A nonlinear soft sensor based on multivariate smoothing procedure for quality estimation in distillation columns , 2000 .

[12]  Niels Kjølstad Poulsen,et al.  New developments in state estimation for nonlinear systems , 2000, Autom..

[13]  M. A. Abdelghani-Idrissi,et al.  Heat exchanger Kalman filtering with process dynamic acknowledgement , 2004, Comput. Chem. Eng..

[14]  Paulo Seleghim,et al.  Inverse measurement method for detecting bubbles in a fluidized bed reactor—toward the development of an intelligent temperature sensor , 2006 .

[15]  D. Luenberger.  An introduction to observers , 1971 .

[16]  M. Soroush.  Nonlinear state-observer design with application to reactors , 1997 .

[17]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[18]  Hsiao-Ping Huang,et al.  A sliding observer for nonlinear process control , 1997 .

[19]  Rubens Maciel Filho,et al.  Soft sensors development for on-line bioreactor state estimation , 2000 .

[20]  H. S. Goldberg.  What is virtual instrumentation , 2000 .

[21]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[22]  Derek Geldart,et al.  The effect of particle size and size distribution on the behaviour of gas-fluidised beds , 1972 .

[23]  Robert R. Bitmead,et al.  State estimation for linear systems with state equality constraints , 2007, Autom..

[24]  D. Simon,et al.  Kalman filtering with state equality constraints , 2002 .