面向显式MPC中显性多面体复杂度的降低

Juraj Števek, M. Kvasnica, M. Fikar
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引用次数: 4

摘要

本文提出了一种基于显性多面体的显式MPC复杂度降低方法。当显式MPC的划分由许多小区域和一个大区域组成时,在控制执行过程中,与大区域相关的控制律比其他控制律调用更频繁是合理的。这样的区域组织有利于在线评估明确的MPC。本文研究了在具有相同仿射控制律的区域上寻找优势多面体的问题。在非凸区域内寻找最大体积多面体的问题在文献中称为马铃薯削皮问题。本文的重点是用随机搜索的方法寻找次优解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a dominant-polytope complexity reduction in explicit MPC
In this paper a complexity reduction method of explicit MPC based on a dominant polytope is proposed. When a partitioning of explicit MPC consists of many small regions and a single big region it is reasonable to expect more frequent call of the control law associated with the big region than another ones during the control performance. Such an organization of the regions favors the online evaluation of explicit MPC. In the paper a problem to find a dominant polytope over the regions that share the same affine control law is studied. The problem of finding maximum volume polytope inscribed in nonconvex area is known as potato peeling problem in the literature. In this paper we focus to find a suboptimal solution by means of stochastic search.
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