Nonlinear Model Predictive Control with aggregated constraints

被引：0

作者：

Pereira, Mateus de Freitas Virgilio ^{[1
]}

Kolmanovsky, Ilya V. ^{[1
]}

Cesnik, Carlos E.S. ^{[1
]}

机构：

[1] Department of Aerospace Engineering, University of Michigan, 1320 Beal Avenue, Ann Arbor,MI,48109, United States

来源：

Automatica | 2022年 / 146卷

关键词：

Closed loop systems - Large scale systems - Nonlinear systems - Predictive control systems - Sensitivity analysis;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper presents a constraint aggregation approach for Nonlinear Model Predictive Control (NMPC). Constraint aggregation functions provide an approximation of the feasible region with a reduced number of nonlinear constraints. The effect of the aggregation on the closed-loop system performance and stability is studied using tools from sensitivity analysis. Numerical results for the control of a 20th order flexible aircraft model show that significant computational savings can be achieved. The proposed method can facilitate the implementation of NMPC solutions for large-scale systems. © 2022 Elsevier Ltd

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