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

被引：0
作者：
Sirine T.B. [1 ]
Badreddine B. [1 ,2 ]
Faouzi B. [1 ]
机构：
[1] LR11ES20, Laboratory of Analysis Conception and Control of Systems, Tunis El Manar University, National Engineering School of Tunis (ENIT)
[2] University of Sousse, National Engineering School of Sousse, Sousse)
来源：
International Journal of Automation and Control | 2019年 / 13卷 / 03期
关键词：
Altium designer; Field-programmable gate array; FPGA; Model predictive control; MPC; PID controller; Predictive control; Quadratic optimisation problem;
D O I：
10.1504/IJAAC.2019.098584
中图分类号：
学科分类号：
摘要：
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. © 2019 Inderscience Enterprises Ltd.
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页码：301 / 323
页数：22
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