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Article
Publication date: 28 March 2022

Yunfei Li, Shengbo Eben Li, Xingheng Jia, Shulin Zeng and Yu Wang

The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic…

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Abstract

Purpose

The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research.

Design/methodology/approach

In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method.

Findings

This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method.

Research limitations implications

Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment.

Originality value

This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.

Details

Journal of Intelligent and Connected Vehicles, vol. 5 no. 2
Type: Research Article
ISSN: 2399-9802

Keywords

Available. Content available
Article
Publication date: 3 April 2009

Jun Jin

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Abstract

Details

Journal of Knowledge-based Innovation in China, vol. 1 no. 2
Type: Research Article
ISSN: 1756-1418

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