DocumentCode :
2858798
Title :
An adaptive predictor corrector strategy for output feedback control of nonlinear hybrid process systems
Author :
Ye Hu ; El-Farra, Nael H.
Author_Institution :
Dept. of Chem. Eng. & Mater. Sci., Univ. of California, Davis, CA, USA
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
2031
Lastpage :
2036
Abstract :
This work presents a methodology for model-based output feedback control of uncertain nonlinear hybrid process systems using an adaptive predictor corrector strategy. A hybrid monitoring scheme is initially developed to facilitate the identification of the active mode at any given time using the measured output. A set of stabilizing output feedback con trollers are then synthesized to robustly stabilize the constituent modes where appropriate state estimators are used. To stabilize each mode with minimal sensor-controller communication, a predictive model of each mode is embedded within the corresponding state feedback controller to provide an estimate of the process state which is used during periods of communication suspension. To determine when the communication must be restored, the evolution of the state estimate for the active mode is monitored and the corresponding state estimator is prompted to send its estimate to update the model state only when some update criteria are satisfied. The key idea is to use the model as a predictor and to use the Lyapunov stability constraint for each mode as a criterion for adaptively correcting the model predictions. The implementation of the proposed methodology is demonstrated using a simulated model of a chemical reactor with multiple operating modes.
Keywords :
Lyapunov methods; nonlinear control systems; stability; state estimation; state feedback; uncertain systems; Lyapunov stability constraint; adaptive predictor corrector; hybrid monitoring; minimal sensor-controller communication; model-based output feedback control; output feedback controllers; predictive model; state estimators; state feedback controller; uncertain nonlinear hybrid process systems; Adaptation models; Lyapunov methods; Observers; Output feedback; Process control; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5991502
Filename :
5991502
Link To Document :
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