Robust Real-Time Model Predictive Control for Torsional Vibration System

Sungwan Boksuwan; Taworn Benjanarasuth

doi:10.20965/ijat.2012.p0345

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IJAT Vol.6 No.3 pp. 345-353

doi: 10.20965/ijat.2012.p0345

(2012)

Paper:

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Robust Real-Time Model Predictive Control for Torsional Vibration System

Sungwan Boksuwan and Taworn Benjanarasuth

Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, 1 Chalongkrung Soi 1, Ladkrabang District, Bangkok, Thailand

Received:

November 17, 2011

Accepted:

January 17, 2012

Published:

May 5, 2012

Keywords:

explicit MPC, two-mass system, Kalman filter, self-optimizing variable, convex optimization, embedded system

Abstract

In this paper, explicit, robust Model Predictive Control (MPC) is proposed for the control of a two-mass system in order to achieve not only good tracking performance and load-change effect rejection, but also low torsional vibration, when the measurement noise contains outliers. The control structure presented in this paper is based fundamentally on the combination of explicit MPC and region detection via a self-optimizing variable. In addition, the well-known Kalman filter is replaced by the robust Kalman filter to deal with the outlier signals. The effectiveness of the proposed method is compared with a PID-based control.

Cite this article as:

Sungwan Boksuwan and Taworn Benjanarasuth, “Robust Real-Time Model Predictive Control for Torsional Vibration System,” Int. J. Automation Technol., Vol.6, No.3, pp. 345-353, 2012.

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References

[1] G. Zhang and J. Furusho, “Speed Control of Two-inertia System by PI/PID Control,” IEEE Trans. Ind. Electron., Vol.47, No.3, pp. 603-609, 2000.
[2] R. Muszynski and J. Deskur, “Damping of Torsional Vibrations in High Dynamic Industrial Drives,” IEEE Trans. Ind. Electron., Vol.57, No.2, pp. 544-552, 2010.
[3] S. Qin and T. Badgwell, “A Survey of Industrial Model Predictive Control Technology,” Control Engineering Practice, Vol.11, pp. 733-764, 2003.
[4] M. T. Cychowski and K. Szabat, “Efficient Real-time Model Predictive Control of the Drive System with Elastic Transmission,” IET Control Theory and Applications, Vol.4, pp. 37-49, 2010.
[5] P. Serkies, T. Orlowska-Kowalska, M. Cychowski, and K. Szabat, “Robust Control of the Two-mass Drive System using Model Predictive Control,” Robust Control, Theory and Applications, Andrzej Bartoszewicz (Ed.), InTech,
Available from: http://www.intechopen.com/articles/show/title/robust-control-of-the-two-mass-drive-system-using-modelpredictive-control.
[6] G. W. Adrian, B. Dale, J. F. Andrew, N. Brett, and S. O. Reza Moheimani, “Model Predictive Control Applied to Constraint Handling in Active Noise and Vibration Control,” IEEE Trans. Control System Technology., Vol.16, No.1, pp. 3-12, 2008.
[7] S. Skogestad, “Simple Analytic Rules for Model Reduction and PID Controller Tuning,” J. of Process Control, Vol.13, pp. 291-309, 2003.
[8] M. Kvasnica, P. Grieder, M. Baotic, and M. Morari, “Multiparametric Toolbox (MPT),”
url: http://control.ee.ethz.ch/˜mpt/.
[9] H. Manum, S. Narasimhan, and S. Skogestad, “A New Approach to Explicit MPC using Self-optimizing Control,” Proc. of the American Control Conf., Washington, USA, 11-13 June 2008, pp. 435-440, 2008.
[10] S. Boyd and J. Mattingley, “Real-time Convex Optimization in Signal Processing,” IEEE Signal Processing Mag., Vol.27, No.3, pp. 50-61, 2010.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] G. Zhang and J. Furusho, “Speed Control of Two-inertia System by PI/PID Control,” IEEE Trans. Ind. Electron., Vol.47, No.3, pp. 603-609, 2000.

[2] [2] R. Muszynski and J. Deskur, “Damping of Torsional Vibrations in High Dynamic Industrial Drives,” IEEE Trans. Ind. Electron., Vol.57, No.2, pp. 544-552, 2010.

[3] [3] S. Qin and T. Badgwell, “A Survey of Industrial Model Predictive Control Technology,” Control Engineering Practice, Vol.11, pp. 733-764, 2003.

[4] [4] M. T. Cychowski and K. Szabat, “Efficient Real-time Model Predictive Control of the Drive System with Elastic Transmission,” IET Control Theory and Applications, Vol.4, pp. 37-49, 2010.

[5] [5] P. Serkies, T. Orlowska-Kowalska, M. Cychowski, and K. Szabat, “Robust Control of the Two-mass Drive System using Model Predictive Control,” Robust Control, Theory and Applications, Andrzej Bartoszewicz (Ed.), InTech,
Available from: http://www.intechopen.com/articles/show/title/robust-control-of-the-two-mass-drive-system-using-modelpredictive-control.

[6] [6] G. W. Adrian, B. Dale, J. F. Andrew, N. Brett, and S. O. Reza Moheimani, “Model Predictive Control Applied to Constraint Handling in Active Noise and Vibration Control,” IEEE Trans. Control System Technology., Vol.16, No.1, pp. 3-12, 2008.

[7] [7] S. Skogestad, “Simple Analytic Rules for Model Reduction and PID Controller Tuning,” J. of Process Control, Vol.13, pp. 291-309, 2003.

[8] [8] M. Kvasnica, P. Grieder, M. Baotic, and M. Morari, “Multiparametric Toolbox (MPT),”
url: http://control.ee.ethz.ch/˜mpt/.

[9] [9] H. Manum, S. Narasimhan, and S. Skogestad, “A New Approach to Explicit MPC using Self-optimizing Control,” Proc. of the American Control Conf., Washington, USA, 11-13 June 2008, pp. 435-440, 2008.

[10] [10] S. Boyd and J. Mattingley, “Real-time Convex Optimization in Signal Processing,” IEEE Signal Processing Mag., Vol.27, No.3, pp. 50-61, 2010.