Quasi-Infinite Adaptive Horizon Nonlinear Model Predictive Control

被引：4

作者：

Griffith, Devin W. ^{[1
]}

Patwardhan, Sachin C. ^{[2
]}

Biegler, Lorenz T. ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 USA

[2] Indian Inst Technol, Dept Chem Engn, Bombay, Maharashtra, India

来源：

IFAC PAPERSONLINE | 2018年 / 51卷 / 18期

基金：

美国国家科学基金会;

关键词：

predictive control; process control; robust stability; nonlinear control; nonlinear programming; model-based control; multivariable feedback control;

D O I：

10.1016/j.ifacol.2018.09.374

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this work we present a new method for calculating terminal conditions for nonlinear model predictive control (NMPC) that is non-conservative and scalable via the quasi infinite horizon methodology. Then, we introduce adaptive-horizon NMPC, a new method for updating prediction horizon lengths online via nonlinear programming sensitivity calculations. Finally, we show how these methods work together to provide an adaptive horizon NMPC implementation for a quad-tank simulation example. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：506 / 511

页数：6

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