ERKAN KAPLANOĞLU, TANER ARSAN, HÜSEYİN SELÇUK VAROL

Predictive control of a constrained pressure and level system

The focus of this paper is the implementation of a constrained predictive control algorithm implemented in Multi-Parametric Toolbox (MPT), which is a free MATLAB toolbox for design, analysis, and implementation of controllers for constrained linear, nonlinear, and hybrid systems. In general, MPT is used for modeling systems offline. The novelty of this study is that real-time mode MPT is used in process control. We also combined the Model Predictive Control Toolbox with MPT. This novel controller is considered a real-time controller of level-pressure systems. In this study, a special type of model predictive control algorithm, the constrained continuous-time generalized control, is used as a controller. The advantages of the controller are illustrated by comparing it to a decoupling PI control.

Anahtar Kelimeler:

Decoupling of systems, level control, predictive control, pressure control, proportional control

Predictive control of a constrained pressure and level system

Keywords:

Decoupling of systems, level control, predictive control, pressure control, proportional control,

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Magni L, Raimondo DM, Allg¨ower F. Nonlinear Model Predictive Control: Towards New Challenging Applications. Berlin, Germany: Springer, 2009.
Kvasnica M, Grieder P, Baotic M, Morari M. Stabilizing low complexity feedback control of constrained piecewise affine systems. Automatica 2005; 41: 1863–1694.
Kaplanoglu E, Safak KK, Varol HS. Real-time parameter estimation method applied to a MIMO process and its comparison with an offline identification method. IAENG Transactions on Engineering Technologies 2009; 1: 35–45.
Kvasnica M. Real-time Model Predictive Control via Multi-parametric Programming. Saarbr¨ucken, Germany: Verlag VDM, 2009.
Zhu Y. Multivariable System Identification for Process Control. Oxford, UK: Elsevier, 2001.
Skogestad S, Postlethwaite I. Multivariable Feedback Control Analysis and Design. New York, NY, USA: Wiley, 19 Recica V. Automatic tuning of multivariable controllers. MSc, Lund Institute of Technology, Sweden, 1998.
Kaplanoglu E, Varol HA, Varol HS. Trajectory tracking multivariable decoupling-pi control for a quadruple-tank system. IKS Proceeding of 2nd International Conference Intelligent Knowledge Systems; 6–8 June 2008; ˙Istanbul, Turkey: pp 68–73.
Johansson KH. The quadruple-tank process: a multivariable laboratory process with an adjustable zero. IEEE Transaction on Control Systems Technology 2000; 3: 456–465.
Astrom KJ, Johansson KH, Wang QG. Design of decoupled PI controllers for two-by-two systems. Control Theory and Applications 2002; 149: 74–81.
Demircioglu H, Gawthrop PJ. Continuous-time generalized predictive control (CGPC). Automatica 1991; 1: 55–74.
Gawthrop PJ, Demircio˘glu H, Siler-Alaca I. Multivariable continuous-time generalized predictive control: A state space approach to linear and nonlinear systems. IEEE Proc-Control Theory and Applications 1998; 145: 241–250.
Camacho FE, Bordons C. Model Predictive Control. London, UK: Springer, 2000.
Mayne DQ, Rakovi´c SV, Findeisen R, Allg¨ower F. Robust output feedback model predictive control of constrained linear systems. Automatica 2006; 42: 1217–1222.
Ronco E, Arsan T, Gawthrop PJ. Open-loop intermittent feedback control practical continuous-time GPC. IEE Proceedings of Control, Theory and Applications 1999; 146: 426–434.
G¨ok¸ce D. Model predictive controller design of hydrocracker reactors. Turk J Elec Eng & Comp Sci 2011; 19: 817–825.
Demircioglu H. Constrained continuous-time generalized predictive control. IEE Proc Control Theory Application 1999; 146: 470–476.
Demircioglu H, Yavuzyılmaz C. Constrained predictive control in continuous time. IEEE Control Systems Magazine 2002; 22: 57–67.