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Nonlinear predictive control of systems exhibiting input multiplicities using the multimodel approach

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Title Nonlinear predictive control of systems exhibiting input multiplicities using the multimodel approach
 
Creator KUMAR, KK
PATWARDHAN, SC
 
Subject models
 
Description This work establishes the feasibility of using a multilayer perceptron for the development of a multimodel that combines structurally simple local models developed in different operating regions. The local models either are obtained by linearizing a first principles model or are identified from input-output data using a linear combination of Laguerre filters. In particular, it is shown that the proposed multimodels can capture dynamic and steady-state characteristics of a continuous fermenter, which exhibit input multiplicities and change in the sign of steady-state gains, fairly accurately over a wide operating range. The proposed multimodel is further used to develop a nonlinear model predictive control (NMPC) scheme. The effectiveness of the NMPC scheme is demonstrated by simulating a servo problem that requires the fermenter to be controlled at its optimum operating point, which happens to be singular points where the invertibility is lost. The proposed NMPC scheme is found to achieve a smooth transition for large-magnitude setpoint changes and control the systems at the singular operating point even in the presence of measurement noise. The NMPC scheme is also found to be robust to moderate variations in system parameters.
 
Publisher AMER CHEMICAL SOC
 
Date 2011-07-14T14:01:04Z
2011-12-26T12:48:25Z
2011-12-27T05:37:33Z
2011-07-14T14:01:04Z
2011-12-26T12:48:25Z
2011-12-27T05:37:33Z
2002
 
Type Article
 
Identifier INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 41(13), 3186-3198
0888-5885
http://dx.doi.org/10.1021/ie001049g
http://dspace.library.iitb.ac.in/xmlui/handle/10054/3975
http://hdl.handle.net/10054/3975
 
Language en