吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (4): 1042-1050.doi: 10.13229/j.cnki.jdxbgxb201404022

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Hardware implementation method for model predictive control on a FPGA chip

XU Fang1, 2, JIN Wei-wei2, CHEN Hong1, 2, ZHANG Zhen-wei2   

  1. 1.State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2.College of Communication Engineering, Jilin University, Changchun 130022, China
  • Received:2013-03-11 Online:2014-07-01 Published:2014-07-01

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Abstract: Miniaturization and high computational performance are demanded when Model Predictive Control (MPC) is applied to fast dynamic system. In order to meet these requirements, a novel hardware implementation method for MPC on a Field Programmable Gate Array (FPGA) chip is proposed. The Particle Swarm Optimization (PSO) algorithm is employed to solve the Quadratic Programming (QP) problem formed in MPC. By analyzing the characteristics, the MPC algorithm is optimized by parallelism-loop unrolling and pipelining to obtain an optimal MPC controller. Real-time simulation tests of electronic throttle control are performed to verify the MPC controller. The results show that the proposed scheme can improve the computational performance of MPC.

Key words: automatic control technology, model predictive control, particle swarm optimization, field programmable gate array, hardware implementation

CLC Number: 

  • TP273
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