Research on probabilistic methods for control system design

被引：128
作者：
Calafiore, Giuseppe C. [2 ]
Dabbene, Fabrizio [1 ]
Tempo, Roberto [1 ]
机构：
[1] Politecn Torino, IEIIT CNR, I-10129 Turin, Italy
[2] Politecn Torino, Dipartimento Automat & Informat, I-10129 Turin, Italy
来源：
AUTOMATICA | 2011年 / 47卷 / 07期
关键词：
Randomized algorithms; Control of uncertain systems; Optimization; CLASSICAL ROBUSTNESS MARGINS; CUTTING PLANE METHOD; RANDOMIZED ALGORITHMS; MONTE-CARLO; APPROXIMATE FEASIBILITY; UNIFORM-DISTRIBUTION; PERFORMANCE; BOUNDS; OPTIMIZATION; CONVERGENCE;
D O I：
10.1016/j.automatica.2011.02.029
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel approach based on probability and randomization has emerged to synergize with the standard deterministic methods for control of systems with uncertainty. The main objective of this paper is to provide a broad perspective on this area of research known as "probabilistic robust control", and to address in a systematic manner recent advances. The focal point is on design methods, based on the interplay between uncertainty randomization and convex optimization, and on the illustration of specific control applications. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1279 / 1293
页数：15
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