Optimized FPGA Implementation of Model Predictive Control for Embedded Systems Using High-Level Synthesis Tool

Lucia, S. ; Navarro, D. (Universidad de Zaragoza) ; Lucia, O. (Universidad de Zaragoza) ; Zometa, P. ; Findeisen, R.

Resumen: Model 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.

Idioma: Inglés

DOI: 10.1109/TII.2017.2719940

Año: 2018

Publicado en: IEEE Transactions on Industrial Informatics 14, 1 (2018), 137-145
ISSN: 1551-3203

Factor impacto JCR: 7.377 (2018)

Categ. JCR: AUTOMATION & CONTROL SYSTEMS rank: 3 / 62 = 0.048 (2018) - Q1 - T1
Categ. JCR: ENGINEERING, INDUSTRIAL rank: 1 / 46 = 0.022 (2018) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 4 / 106 = 0.038 (2018) - Q1 - T1

Factor impacto SCIMAGO: 1.678 - Computer Science Applications (Q1) - Information Systems (Q1) - Electrical and Electronic Engineering (Q1) - Control and Systems Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/FSE
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TEC2016-78358-R

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Tecnología Electrónica (Dpto. Ingeniería Electrón.Com.)