FPGA Implementation of Nonlinear Model Predictive Control

被引：0
作者：
Xu, Fang [1 ,2 ]
Chen, Hong [1 ,2 ]
Jin, Weiwei [2 ]
Xu, Yueting [2 ]
机构：
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130025, Peoples R China
[2] Jilin Univ, Dept Control Sci & Engn, Changchun 130025, Peoples R China
来源：
26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC) | 2014年
关键词：
Nonlinear Model Predictive Control; Optimization Problem; Particle Swarm Optimization and Field Programrnnable Gate Array; OPTIMIZATION; DESIGN;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The online computational burden associated with the solution of the NMPC optimization problem is a key issue when applying nonlinear model predictive control (MPC) to fast dynamic systems. In order to improve the computation efficiency, a novel hardware implementation method for NMPC on a field programmable gate array (FPGA) chip is proposed. The optimization problem formed by NMPC is solved by particle swarm optimization (PSO) algorithm. The process speed of NMI(: can be accelerated by exploring the parallelism-loop unrolling and pipelining architecture. Real-time simulation test of engine idle speed control (ISC) is performed to verify the NMPC controller. The results show that the designed NMPC-FPGA controller can achieve satisfactory performance for ISC.
引用
收藏
页码：108 / 113
页数：6
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