Economic Model Predictive Control of Sampled-Data Linear Systems With Piecewise Constant Control

被引：1

作者：

Liang, Haojiao ^{[1
]}

Li, Huiping ^{[1
]}

Xu, Demin ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Shaanxi, Peoples R China

来源：

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME | 2019年 / 141卷 / 12期

基金：

中国国家自然科学基金;

关键词：

TO-STATE-STABILITY; OPTIMIZATION;

D O I：

10.1115/1.4044357

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 paper studies an economic model predictive control (EMPC) problem for sampled-data linear systems with system constraints. The cost function consists of an economic part and a regulatory part, and a new EMPC algorithm with piecewise constant control is designed. Iterative feasibility of the designed optimization problem and input-to-state stability (ISS) of the closed-loop system are proved. In particular, we show that the closed-loop system is input-to-state stable with respect to the supremum norm of the economic cost, and the system state is ultimately bounded within a bound determined by the economic cost. Through thorough simulations, the effectiveness of the designed algorithm is verified and the tradeoff between control and economic performance is demonstrated.

引用

页数：8

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