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State estimation and nonlinear predictive control of autonomous hybrid system using derivative free state estimators

DSpace at IIT Bombay

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Title State estimation and nonlinear predictive control of autonomous hybrid system using derivative free state estimators
 
Creator PRAKASH, J
PATWARDHAN, SC
SHAH, SL
 
Subject kalman filter
scheme
ensemble kalman filter
unscented kalman filter
autonomous hybrid system
nonlinear model predictive controller
state estimation based nmpc
 
Description In this work, we develop a state estimation scheme for nonlinear autonomous hybrid systems, which are subjected to stochastic state disturbances and measurement noise, using derivative free state estimators. In particular, we propose the use of ensemble Kalman filters (EnKF), which belong to the class of particle filters, and unscented Kalman filters (UKF) to carry out estimation of state variables of autonomous hybrid system. We then proceed to develop novel nonlinear model predictive control (NMPC) schemes using these derivative free estimators for better control of autonomous hybrid systems. A salient feature of the proposed NMPC schemes is that the future trajectory predictions are based on stochastic simulations, which explicitly account for the uncertainty in predictions arising from the uncertainties in the initial state and the unmeasured disturbances. The efficacy of the proposed state estimation based control scheme is demonstrated by conducting simulation studies on a benchmark three-tank hybrid system. Analysis of the simulation results reveals that EnKF and UKF based NMPC strategies is well suited for effective control of nonlinear autonomous three-tank hybrid system.
 
Publisher ELSEVIER SCI LTD
 
Date 2011-07-22T13:26:52Z
2011-12-26T12:52:26Z
2011-12-27T05:37:49Z
2011-07-22T13:26:52Z
2011-12-26T12:52:26Z
2011-12-27T05:37:49Z
2010
 
Type Article
 
Identifier JOURNAL OF PROCESS CONTROL, 20(7), 787-799
0959-1524
http://dx.doi.org/10.1016/j.jprocont.2010.04.001
http://dspace.library.iitb.ac.in/xmlui/handle/10054/6243
http://hdl.handle.net/10054/6243
 
Language en