Probabilistic Constrained MPC for Multiplicative and Additive Stochastic Uncertainty

被引：125
|
作者：
Cannon, Mark [1 ]
Kouvaritakis, Basil [1 ]
Wu, Xingjian [1 ]
机构：
[1] Univ Oxford, Dept Engn Sci, Oxford OX1 3PJ, England
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2009年 / 54卷 / 07期
关键词：
Constrained control; fatigue life; optimization; stochastic control; MODEL-PREDICTIVE CONTROL;
D O I：
10.1109/TAC.2009.2017970
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 technical note develops a receding horizon control strategy to guarantee closed-loop convergence and feasibility in respect of soft constraints. Earlier results [1] addressed the case of multiplicative uncertainty only. The present technical note extends these to the more general case of additive and multiplicative uncertainty and proposes a method of handling probabilistic constraints. The results are illustrated by a simple design study considering the control of a wind turbine.
引用
收藏
页码：1626 / 1632
页数：7
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