IJAT Vol.6 No.3 pp. 345-353
doi: 10.20965/ijat.2012.p0345


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

November 17, 2011
January 17, 2012
May 5, 2012
explicit MPC, two-mass system, Kalman filter, self-optimizing variable, convex optimization, embedded system

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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