Model predictive control design for linear parameter varying systems: A survey

被引：128
作者：
Morato, Marcelo M. [1 ]
Normey-Rico, Julio E. [1 ]
Sename, Olivier [2 ]
机构：
[1] Univ Fed Santa Catarina, Dept Autom & Sist DAS, Renewable Energy Res Grp GPER, Florianopolis, SC, Brazil
[2] Univ Grenoble Alpes, Grenoble INP, GIPSA Lab, CNRS,Inst Engn, F-38000 Grenoble, France
来源：
ANNUAL REVIEWS IN CONTROL | 2020年 / 49卷
关键词：
Model predictive control; Linear parameter varying systems; Optimization; Quadratic programming; Survey; DISCRETE-TIME-SYSTEMS; CONSTRAINED NONLINEAR-SYSTEMS; FAULT-TOLERANT CONTROL; FEEDBACK ROBUST MPC; TUBE-BASED MPC; LPV SYSTEMS; CONTROL STRATEGY; INVARIANT-SETS; BOUNDED RATES; STABILITY;
D O I：
10.1016/j.arcontrol.2020.04.016
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Motivated by the fact that many nonlinear plants can be represented through Linear Parameter Varying (LPV) embedding, and being this framework very popular for control design, this paper investigates the available Model Predictive Control (MPC) policies that can be applied for such systems. This paper reviews the available works considering LPV MPC design, ranging from the sub-optimal, simplified, yet Quadratic Programming (QP) algorithms, the tube-based tools, the set-constrained procedures, the Nonlinear Programming procedures and the robust ones; the main features of the recent research body on this topic are examined. A simulation example is given comparing some of the important techniques. Finally, some suggestions are given for future investigation threads, seeking further applicability of these methods. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码：64 / 80
页数：17
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