A Data-Driven Predictive Control Structure in the Behavioral Framework

被引：7
|
作者：
Wei, Lai [1 ]
Yan, Yitao [1 ]
Bao, Jie [1 ]
机构：
[1] Univ New South Wales, Sch Chem Engn, Sydney, NSW 2052, Australia
来源：
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
基金：
澳大利亚研究理事会;
关键词：
data-driven predictive control; behavioral systems theory; dissipativity; DISSIPATIVE DYNAMICAL-SYSTEMS;
D O I：
10.1016/j.ifaco1.2020.12.113
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a data-driven predictive control (DPC) algorithm for linear time-invariant (LTI) systems in the behavioral framework. The system is described by the parametrization of the Hankel matrix constructed from its measured trajectories. The proposed structure follows a two-step procedure. The existence of a controlled behavior is firstly verified from the perspective of dissipativity with the aid of quadratic difference forms (QdFs), then the controlled trajectory is selected from the original uncontrolled behavior through optimization. An illustrative example is presented to demonstrate the effectiveness of the proposed approach. Copyright (C) 2020 The Authors.
引用
收藏
页码：159 / 164
页数：6
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