Publication
Embedded optimization-based controllers for industrial processes
Conference Article
Conference
IEEE Colombian Conference on Automatic Control (CCAC)
Edition
3rd
Pages
1-6
Doc link
http://dx.doi.org/10.1109/CCAC.2017.8276432
File
Abstract
Due to the growth of computational capabilities and the proliferation of field-programmable gate arrays (FPGA), the utilization of model predictive control (MPC) for embedded applications in the industry has become a possibility and a fact. This paper presents and discusses the possibilities of the use of online MPC, embedded in an educational device from National Instruments, using two different optimization algorithms and code generators, which have come out in recent years by the academia: CVXGEN, which implements a primal-dual interior-point algorithm, and qpOASES, which relies on the online active-set strategy algorithm. Both algorithms have been tested both in simulation and in real-time experimentation to control a four-tank pilot plant.
Categories
automation, control theory, optimisation.
Author keywords
real-time control, industrial process, four-tanks system, myRio device
Scientific reference
C. Ibáñez, C. Ocampo-Martínez and B. González. Embedded optimization-based controllers for industrial processes, 3rd IEEE Colombian Conference on Automatic Control, 2017, Cartagena, pp. 1-6.
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