000071047 001__ 71047
000071047 005__ 20190709135640.0
000071047 0247_ $$2doi$$a10.1109/TII.2017.2719940
000071047 0248_ $$2sideral$$a104243
000071047 037__ $$aART-2018-104243
000071047 041__ $$aeng
000071047 100__ $$aLucia, S.
000071047 245__ $$aOptimized FPGA Implementation of Model Predictive Control for Embedded Systems Using High-Level Synthesis Tool
000071047 260__ $$c2018
000071047 5060_ $$aAccess copy available to the general public$$fUnrestricted
000071047 5203_ $$aModel predictive control (MPC) is an optimization-based strategy for high-performance control that is attracting increasing interest. While MPC requires the online solution of an optimization problem, its ability to handle multivariable systems and constraints makes it a very powerful control strategy specially for MPC of embedded systems, which have an ever increasing amount of sensing and computation capabilities. We argue that the implementation of MPC on field programmable gate arrays (FPGAs) using automatic tools is nowadays possible, achieving cost-effective successful applications on fast or resource-constrained systems. The main burden for the implementation of MPC on FPGAs is the challenging design of the necessary algorithms. We outline an approach to achieve a software-supported optimized implementation of MPC on FPGAs using high-level synthesis tools and automatic code generation. The proposed strategy exploits the arithmetic operations necessaries to solve optimization problems to tailor an FPGA design, which allows a tradeoff between energy, memory requirements, cost, and achievable speed. We show the capabilities and the simplicity of use of the proposed methodology on two different examples and illustrate its advantages over a microcontroller implementation.
000071047 536__ $$9info:eu-repo/grantAgreement/ES/DGA/FSE$$9info:eu-repo/grantAgreement/ES/MINECO/TEC2016-78358-R
000071047 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000071047 590__ $$a7.377$$b2018
000071047 591__ $$aAUTOMATION & CONTROL SYSTEMS$$b3 / 62 = 0.048$$c2018$$dQ1$$eT1
000071047 591__ $$aENGINEERING, INDUSTRIAL$$b1 / 46 = 0.022$$c2018$$dQ1$$eT1
000071047 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b4 / 106 = 0.038$$c2018$$dQ1$$eT1
000071047 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000071047 700__ $$0(orcid)0000-0002-0795-8743$$aNavarro, D.$$uUniversidad de Zaragoza
000071047 700__ $$0(orcid)0000-0002-1284-9007$$aLucia, O.$$uUniversidad de Zaragoza
000071047 700__ $$aZometa, P.
000071047 700__ $$aFindeisen, R.
000071047 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica
000071047 773__ $$g14, 1 (2018), 137-145$$pIEEE Trans. Ind. Inform.$$tIEEE Transactions on Industrial Informatics$$x1551-3203
000071047 8564_ $$s810809$$uhttp://zaguan.unizar.es/record/71047/files/texto_completo.pdf$$yPostprint
000071047 8564_ $$s121176$$uhttp://zaguan.unizar.es/record/71047/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000071047 909CO $$ooai:zaguan.unizar.es:71047$$particulos$$pdriver
000071047 951__ $$a2019-07-09-12:37:52
000071047 980__ $$aARTICLE