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Kalman filtering approaches for solving problems in analytical chemistry
Author(s) -
Rutan Sarah C.
Publication year - 1987
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180010104
Subject(s) - kalman filter , fast kalman filter , least squares function approximation , extended kalman filter , computer science , invariant extended kalman filter , non linear least squares , nonlinear system , algorithm , calibration , alpha beta filter , compensation (psychology) , mathematics , estimation theory , moving horizon estimation , statistics , artificial intelligence , physics , psychology , quantum mechanics , estimator , psychoanalysis
The application of the Kalman filter to the solution of a variety of problems in analytical chemistry is reviewed. Five examples are selected from the literature to illustrate the use of Kalman filtering techniques for obtaining least‐squares estimates fo several parameters of analytical importance. These examples include multicomponent curve resolution and concentration estimation, correction for variable background responses, calibration with drift compensation, and estimation of kinetic parameters for first‐order reactions and for heterogeneous charge‐transfer reactions. An adaptive Kalman filtering technique is required for the solution of the background correction problem, and the extended Kalman filter algorithm is required for the solution of the nonlinear kinetic problems. For each case, the results that were obtained are summarized, and some advantages of Kalman filtering over traditional least‐squares approaches are discussed.