Automatically generated embedded model predictive control: Moving an industrial PC‐based MPC to an embedded platform. (17th June 2015)

• Record Type: Journal Article
• Authors: Kufoalor, D. K. M.; Aaker, V.; Johansen, T. A.; Imsland, L.; Eikrem, G. O.; Jones, Colin N.; Kerrigan, Eric
• Is Part Of: Optimal control applications and methods. Volume 36:Number 5(2015:Sep./Oct.)
• Page Start: 705
• Page End: 727
• Publication Date: 2015-06-17
• Subjects: Control theory -- Periodicals; Mathematical optimization -- Periodicals; 629.8312
• DOI: 10.1002/oca.2182
• Languages: English
• ISSNs: 0143-2087

Abstract

<abstract abstract-type="main" id="oca2182-abs-0001"> <title>Summary</title> <p id="oca2182-para-0001">An embedded model predictive controller (eMPC) based on the linear MPC module in Statoil Estimation and Prediction Tool for Identification and Control has been developed, and it is intended to facilitate the MPC application on embedded hardware. The control design approach illustrates a viable way of migrating from an industrial PC‐based MPC technology to an embedded platform. This work also provides the transformations and the real‐time considerations necessary to achieve a functional high‐performance predictive controller on a low‐cost embedded hardware, with limited computational resources. The eMPC was implemented for rapid prototyping on the Ethernut 5 open‐source hardware, and its performance was tested for a simulated process. The concept was tested using a real MPC application developed for a prototype of a new industrial process that requires an advanced embedded multivariable, constraint handling control solution. The results confirm the viability of the embedded MPC design approach. Copyright © 2015 John Wiley &amp; Sons, Ltd.</p> </abstract>