Output feedback predictive control for hydrographic process

This paper introduces a new output feedback control scheme, which combine nonlinear generalized predictive control (NGPC) with a high gain observer (HGO). We consider the input affine nonlinear MIMO class of systems, that include the model of our hydrographic process. Indeed, from the liquid levels measurements in both bottoms tanks, we reconstruct the levels of both upper ones, and we use them in the state feedback control loop. The predictive control law synthesized is an explicit continuous solution of optimization problem, it arise from receding horizon index minimization. As it is known, to deal with the separation principle requirement, we need to lead the system in the new state coordinate and to impose control constraints. This last can inherently taking into account by the predictive controller, when we reformulate control law through the on-line solution of quadratic programming (QP) problem.

[1]  Henk Nijmeijer,et al.  Observer-based model predictive control , 2004 .

[2]  Manfredi Maggiore,et al.  A separation principle for a class of non-UCO systems , 2003, IEEE Trans. Autom. Control..

[3]  Hassan K. Khalil,et al.  High-gain observers in nonlinear feedback control , 2009, 2009 IEEE International Conference on Control and Automation.

[4]  Hassan Hammouri,et al.  A high gain observer for a class of uniformly observable systems , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[5]  Karl Henrik Johansson,et al.  The quadruple-tank process: a multivariable laboratory process with an adjustable zero , 2000, IEEE Trans. Control. Syst. Technol..

[6]  Peter J. Gawthrop,et al.  Optimal control of nonlinear systems: a predictive control approach , 2003, Autom..

[7]  José Luis Figueroa,et al.  A high gain nonlinear observer: application to the control of an unstable nonlinear process , 2004, Comput. Chem. Eng..

[8]  H. Khalil,et al.  A separation principle for the stabilization of a class of nonlinear systems , 1997 .

[9]  Ping Lu,et al.  Optimal predictive control of continuous nonlinear systems , 1995 .

[10]  J. Gauthier,et al.  A simple observer for nonlinear systems applications to bioreactors , 1992 .

[11]  Zoltan K. Nagy,et al.  Nonlinear model predictive control of a four tank system: an experimental stability study , 2006, 2006 IEEE International Conference on Control Applications.

[12]  F. Allgöwer,et al.  OUTPUT FEEDBACK NONLINEAR PREDICTIVE CONTROL -A SEPARATION PRINCIPLE APPROACH , 2002 .

[13]  Mohammed M'Saad,et al.  Observer design for a class of MIMO nonlinear systems , 2004, Autom..

[14]  P. Young,et al.  An improved structure for model predictive control using non-minimal state space realisation , 2006 .

[15]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[16]  F. Allgöwer,et al.  Output feedback stabilization of constrained systems with nonlinear predictive control , 2003 .

[17]  Hassan K. Khalil High-gain observers in nonlinear feedback control , 2009, ICCA 2009.

[18]  S. H. Said,et al.  Output Feedback Nonlinear GPC Using High Gain Observer , 2007, 2007 International Symposium on Computational Intelligence and Intelligent Informatics.

[19]  D. Mayne,et al.  Robust receding horizon control of constrained nonlinear systems , 1993, IEEE Trans. Autom. Control..

[20]  T. A. Badgwell,et al.  An Overview of Industrial Model Predictive Control Technology , 1997 .

[21]  Wen-Hua Chen,et al.  Predictive control of general nonlinear systems using approximation , 2004 .

[22]  Masoud Soroush,et al.  Input-output linearizing nonlinear model predictive control , 1997 .

[23]  Mondher Farza,et al.  A SET OF OBSERVERS FOR A CLASS OF NONLINEAR SYSTEMS , 2005 .