Title: A hardware/software architecture dedicated to model predictive control law and implemented into an FPGA platform

Authors: Telmoudi Brini Sirine; Bouzouita Badreddine; Bouani Faouzi

Addresses: LR11ES20 Laboratory of Analysis Conception and Control of Systems, Tunis El Manar University, National Engineering School of Tunis (ENIT), Tunisia ' LR11ES20 Laboratory of Analysis Conception and Control of Systems, Tunis El Manar University, National Engineering School of Tunis (ENIT), Tunisia; University of Sousse, National Engineering School of Sousse (Sousse), Tunisia ' LR11ES20 Laboratory of Analysis Conception and Control of Systems, Tunis El Manar University, National Engineering School of Tunis (ENIT), Tunisia

Abstract: Model predictive control (MPC) is an optimisation-based strategy for high-performance control engineering practice and real-time applications. This method needs to solve online a quadratic programming (QP) problem at each sample time to find optimal control sequence. In this paper, a new optimised MPC architecture is presented, for a gradient-based QP solver to implement linear MPC on a field-programmable gate array platform, which allows obtaining high-quality performances for the real-time control applications. It requires a manual programming of the high-level C/C ++ code in opposition to the other presented approaches, which automatically generates the code. The efficiency of this approach is completed with real time control of the water level of a single tank system running on a Nanoboard 3000XN chip using a conception environment (Altium Designer), while comparing between the MPC and PID controllers.

Keywords: field-programmable gate array; FPGA; predictive control; quadratic optimisation problem; PID controller; Altium designer; model predictive control; MPC.

DOI: 10.1504/IJAAC.2019.098584

International Journal of Automation and Control, 2019 Vol.13 No.3, pp.301 - 323

Received: 21 Mar 2017
Accepted: 27 Oct 2017

Published online: 28 Mar 2019 *

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