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Robust stability of nonlinear model predictive control based on extended Kalman filter

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Title Robust stability of nonlinear model predictive control based on extended Kalman filter
 
Creator HUANG, R
PATWARDHAN, SC
BIEGLER, LT
 
Subject EKF
NMPC
Robust stability
DISCRETE-TIME-SYSTEMS
FEEDBACK STABILIZATION
OUTPUT-FEEDBACK
OBSERVERS
 
Description This work deals with state estimation and process control for nonlinear systems, especially when nonlinear model predictive control (NMPC) is integrated with extended Kalman filter (EKF) as the state estimator. In particular, we focus on the robust stability of NMPC and EKF in the presence of plant-model mismatch. The convergence property of the estimation error from the EKE in the presence of non-vanishing perturbations is established based on our previous work [1]. In addition, a so-called one way interaction is shown that the EKE error is not influenced by control action from the NMPC. Hence, the EKF analysis is still valid in the output-feedback NMPC framework, even though there is no separation principle for general nonlinear systems. With this result, we study the robust stability of the output-feedback NMPC under the impact of the estimation error. It turns out the output-feedback NMPC with EKF is Input-to-State practical Stable (ISpS). Finally, two offset-free strategies of output-feedback NMPC are presented and illustrated through a simulation example. (C) 2011 Elsevier Ltd. All rights reserved.
 
Publisher ELSEVIER SCI LTD
 
Date 2014-10-16T12:57:09Z
2014-10-16T12:57:09Z
2012
 
Type Article
 
Identifier JOURNAL OF PROCESS CONTROL, 22(1)82-89
http://dx.doi.org/10.1016/j.jprocont.2011.10.006
http://dspace.library.iitb.ac.in/jspui/handle/100/15604
 
Language en