NDLI: Unconstrained MPC tuning for prediction accuracy in Networked Control Systems

Content Provider	IEEE Xplore Digital Library
Author	Tsoeu, M.S. Koetje, T.
Copyright Year	2011
Description	Author affiliation: Department of Electrical Engineering, Private Bag X3, Rondebosch, 7701, University of Cape Town, South Africa (Tsoeu, M.S.; Koetje, T.)
Abstract	Model Predictive Control (MPC) has received wide attention from both the academic and industrial societies, mainly in the chemical industries, and is fast gaining popularity in Electro-Mechanical industrial systems. Great success stories of applications of MPC to industrial systems have been reported. However, the model based nature of this control methodology raises numerous questions of robustness, mainly towards prediction accuracy. A large amount of research has been conducted in MPC tuning, both mathematically inclined and heuristic. However, most of the works were intended at improving performance and robustness for control systems that are not interconnected over shared networks. In this paper, analysis of the standard tuning parameters of MPC and their effects on prediction accuracy are investigated, implications of such accuracy on Networked Control Systems (NCS) with random data packet dropouts are demonstrated by simulation and experimental studies.
Starting Page	474
Ending Page	479
File Size	923825
Page Count	6
File Format	PDF
ISBN	9781424495702
e-ISBN	9781424495733
DOI	10.1109/ICNSC.2011.5874889
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-11
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Copyright © SinfraS - Society for Infrastructure Systems
Subject Keyword	Accuracy Tuning Predictive models Computational modeling Trajectory Mathematical model NCS Model Predictive Control (MPC) MPC Tuning Prediction Accuracy
Content Type	Text
Resource Type	Article

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