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System and method for solving quadratic programming problems with bound constraints utilizing a semi-explicit quadratic programming solver

机译:利用半显式二次规划求解器求解具有约束约束的二次规划问题的系统和方法

摘要

A system and method for solving a quadratic programming optimization problem with bound constraints using a semi-explicit QP solver with respect to an embedded platform is presented. A linear system of equations associated with a matrix (e.g., a Karush-Kuhn-Tucker matrix, KKT system) can be solved at each iteration of the solver based on a factorization approach. A set of partial factors with respect to the QP problem can be pre-computed off-line and stored into a memory. The factorization process of the KKT matrix can then be finished on-line in each iteration of the semi-explicit QP solver in order to effectively solve the QP optimization problems. The QP problem can be solved utilizing a standard active-set approach and/or a partial explicit approach based on a processor utilization and memory usage.
机译:提出了一种针对嵌入式平台使用半显式QP求解器求解具有约束约束的二次规划优化问题的系统和方法。可以基于分解方法在求解器的每次迭代中求解与矩阵相关联的线性方程组(例如,Karush-Kuhn-Tucker矩阵,KKT系统)。可以离线离线计算与QP问题有关的一组局部因素,并将其存储到内存中。然后可以在半显式QP解算器的每次迭代中在线完成KKT矩阵的分解过程,以便有效地解决QP优化问题。可以使用标准活动集方法和/或基于处理器利用率和内存使用率的部分显式方法来解决QP问题。

著录项

  • 公开/公告号US8924331B2

    专利类型

  • 公开/公告日2014-12-30

    原文格式PDF

  • 申请/专利权人 JAROSLAV PEKAR;ONDREJ SANTIN;

    申请/专利号US20100875239

  • 发明设计人 JAROSLAV PEKAR;ONDREJ SANTIN;

    申请日2010-09-03

  • 分类号G06N5/02;G06F17;G05B13/04;G06F17/11;

  • 国家 US

  • 入库时间 2022-08-21 15:16:57

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