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Robust Real-Time Model Predictive Control for Torsional Vibration System
Author(s) -
Sungwan Boksuwan,
Taworn Benjanarasuth
Publication year - 2012
Publication title -
international journal of automation technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.513
H-Index - 18
eISSN - 1883-8022
pISSN - 1881-7629
DOI - 10.20965/ijat.2012.p0345
Subject(s) - model predictive control , control theory (sociology) , kalman filter , outlier , noise (video) , vibration , pid controller , computer science , robust control , engineering , control system , control engineering , control (management) , artificial intelligence , temperature control , physics , electrical engineering , quantum mechanics , image (mathematics)
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.

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