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Improved State Estimation using a Combination of Moving Horizon Estimator and Particle Filters

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2 Author(s)
Murali R. Rajamani ; PhD student, Faculty, Department of Chemical and Biological Engineering, University of Wisconsin - Madison, 1415 Engineering Drive, Madison, WI 53706. ; James B. Rawlings

State estimation is an important part of advanced process control. A moving horizon estimator (MHE) is often used for state estimation due to its robustness and ease of handling constraints. Sequential Monte-Carlo type techniques for state estimation also called particle niters (PF) are becoming popular due to their speed and ease of implementation. In this paper we present a novel combination of the MHE with the PF to gives a robust fast state estimator. The combined advantages of the MHE and particle filter provide efficient state estimation.

Published in:

2007 American Control Conference

Date of Conference:

9-13 July 2007