Embedded optimization-based controllers for industrial processes
Cita com:
hdl:2117/116534
Tipus de documentText en actes de congrés
Data publicació2017
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
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.
Descripció
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CitacióIbáñez, C., Ocampo-Martinez, C.A., González García, B. Embedded optimization-based controllers for industrial processes. A: Colombian Conference on Automatic Control. "Proceedings of the 3rd IEEE Colombian Conference on Automatic Control". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-6.
Versió de l'editorhttp://ieeexplore.ieee.org/document/8276432/
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