A robust nonlinear tracking MPC using qLPV embedding and zonotopic uncertainty propagation

被引:3
作者
Morato, Marcelo M. [1 ,3 ]
Cunha, Victor M. [2 ]
Santos, Tito L. M. [2 ]
Normey-Rico, Julio E. [1 ]
Sename, Olivier [3 ]
机构
[1] Univ Fed Santa Catarina, Dept Automacao & Sistemas, Florianopolis, Brazil
[2] Univ Fed Bahia, Dept Engn Elect & Comp, Salvador, BA, Brazil
[3] Univ Grenoble Alpes, GIPSA Lab, CNRS, Grenoble INP 1, F-38000 Grenoble, France
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2024年 / 361卷 / 06期
关键词
Model predictive control; Linear parameter varying systems; Nonlinear systems; Tracking; Zonotopes; MODEL-PREDICTIVE CONTROL; MOVING HORIZON ESTIMATION; FAULT-TOLERANT CONTROL; LPV-MPC; STABILITY; SUBJECT; SYSTEMS; DESIGN;
D O I
10.1016/j.jfranklin.2024.106713
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 paper, we propose a novel Nonlinear Model Predictive Control (NMPC) framework for tracking for piece -wise constant reference signals. The main novelty is the use of quasiLinear Parameter Varying (qLPV) embeddings in order to describe the nonlinear dynamics. Furthermore, these embeddings are exploited by an extrapolation mechanism, which provides the future behaviour of the scheduling parameters with bounded estimation error. Therefore, the resulting NMPC becomes computationally efficient (comparable to a Quadratic Programming algorithm), since, at each sampling period, the predictions are linear. Benefiting from artificial target variables, the method is also able to avoid feasibility losses due to large set -point variations. Robust constraint satisfaction, closed -loop stability, and recursive feasibility certificates are provided, thanks to uncertainty propagation zonotopes and parameter -dependent terminal ingredients. A benchmark example is used to illustrate the effectiveness of the method, which is compared to state-of-the-art techniques.
引用
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页数:26
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