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Symmetric Constrained Optimal Control

delete2015-01-01
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OA
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C
Claus Danielson *
F
Francesco Borrelli
DOI:10.1016/j.ifacol.2015.11.307delete
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摘要

摘要

En 中文
This paper extends previous results on symmetry in strictly ex linear odd predictive control to non-strictly convex and nonlinear model predictive control. We define symmetry for constrained systems, controllers, and model predictive control problems. We shove that symmetric model predictive control problems produce symmetric controllers. Vie show that the previously established methods of memory reduction can be applied to non strictly convex problems. We apply these memory reduction techniques to the battery balancing problem. Exploiting symmetry leads to an exponential memory reduction and simple, intuitive optimal controllers. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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期刊

I
IFAC Papers Online
IF:
0
论文数:
985
被引数:
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机构

University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
U
university of california berkeley
学者数:
210
论文数: 113
被引数: 0
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引用论文

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