Brief paper: A parametric programming approach to moving-horizon state estimation

Authors:
Mark L. Darby;Michael Nikolaou
Affiliations:
Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204-4004, USA;Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX 77204-4004, USA
Venue:
Automatica (Journal of IFAC)
Year:
2007

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Abstract

We propose a solution to moving-horizon state estimation that incorporates inequality constraints in both a systematic and computationally efficient way, akin to Kalman filtering. The proposed method allows the on-line constrained optimization problem involved in moving-horizon state estimation to be solved offline, requiring only a look-up table and simple function evaluations for real-time implementation. The method is illustrated via simulations on a system that has been studied in literature.