A dual gradient-projection algorithm for model predictive control in fixed-point arithmetic

被引：16

作者：

Patrinos, Panagiotis ^{[1
]}

Guiggiani, Alberto ^{[1
]}

Bemporad, Alberto ^{[1
]}

机构：

[1] IMT, Inst Adv Studies, I-55100 Lucca, Italy

来源：

AUTOMATICA | 2015年 / 55卷

关键词：

Embedded systems; Convex optimization; Predictive control; MINIMIZATION;

D O I：

10.1016/j.automatica.2015.03.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Although linear Model Predictive Control has gained increasing popularity for controlling dynamical systems subject to constraints, the main barrier that prevents its widespread use in embedded applications is the need to solve a Quadratic Program (QP) in real-time. This paper proposes a dual gradient projection (DGP) algorithm specifically tailored for implementation on fixed-point hardware. A detailed convergence rate analysis is presented in the presence of round-off errors due to fixed-point arithmetic. Based on these results, concrete guidelines are provided for selecting the minimum number of fractional and integer bits that guarantee convergence to a suboptimal solution within a pre-specified tolerance, therefore reducing the cost and power consumption of the hardware device. (C) 2015 Elsevier Ltd. All rights reserved.

引用

下载

页码：226 / 235

页数：10

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