MADS-based fast FPGA implementation of nonlinear model predictive control

被引：2

作者：

Ravera, Alessandro ^{[1
]}

Oliveri, Alberto ^{[1
]}

Lodi, Matteo ^{[1
]}

Storace, Marco ^{[1
]}

机构：

[1] Univ Genoa, Dept Elect Elect Telecommun Engn & Naval Architec, Via Opera Pia 11a, Genoa, Italy

来源：

2023 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS | 2023年

关键词：

nonlinear model predictive control; mesh adaptive direct search; FPGA; FRAMEWORK;

D O I：

10.1109/ISCAS46773.2023.10181647

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the derivative-free optimization algorithm MADS (mesh adaptive direct search) is adapted for implementation on field programmable gate array (FPGA) with fixed-point data representation. MADS is then exploited to solve constrained nonlinear optimization problems arising from nonlinear model predictive control. The application on two examples taken from the literature shows the advantages of the proposed circuit architecture over the existing work, in terms of latency and resource occupation.

引用

页数：5

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