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BMI Global Optimization with Beowulf Cluster and Simultaneous Optimization of Structure-Control

使用 Beowulf 集群的 BMI 全局优化和结构控制的同步优化

基本信息

批准号：
18560435
负责人：
KAWANISHI Michihiro
金额：
$ 2.37万
依托单位：
Toyota Technological Institute
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2006
资助国家：
日本
起止时间：
2006 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18560435/
关键词：
Bilinear matrix inequality Branch and bound method Real-coded genetic algorithm Beowulf cluster computer Parallel distributed calculation Simultaneous optimization BMI BMI

项目摘要

1. Research for BMI optimization with Beowulf cluster(1) A Beowulf cluster computer that enables us to achieve 2[decade] accuracy with 104 CPUs is constructed.(2) On branch and bound method for BMI global optimization, we developed a novel branching operation considering complicating variable dimension which is important on practical problems.(3) For the parallelization of the BMI branch and bound method, we developed parallelized algorithms that realize variable computational granularity. The developed algorithms of the BMI branch and bound are implemented in Beowulf cluster.(4) On real-coded genetic algorithm for BMI optimization, we introduced a reduced-order individual expression and an individual evaluation method using LMI optimization. The developed method enables us to more accurately evaluate individuals compared to conventional eigenvalue-based methods.(5) In order to reduce the computation burden of the developed method (4), we also developed a parallelization algorithm that fully utilizes the computational power of Beowulf cluster.2. Research for simultaneous optimization based on BMI optimization method(1) Parallel-link system is one of the best application of simultaneous optimization due to the complexity of the link structure. The performance of the parallel-link system depends on both controller and link-structure. For redundant parallel-link system, we developed a optimal power distribution control with LMI optimization. However, the globally optimal link-structure and globally optimal control row are not yet obtained.(2) In the practical view point, modeling and parameter tuning are both important for simultaneous optimization design. In the context, we developed a data-based controller design method based on unfalsified control technique and support vector machine. The method clarified the possibility of the data-based simultaneous optimization method.

1. Beowulf集群计算机BMI优化研究（1）构建了一台具有104个CPU的Beowulf集群计算机，使我们能够实现2[decade]精度。(2)在BMI全局优化的分支定界方法中，考虑到变维问题的复杂性，提出了一种新的分支操作。(3)为了实现BMI分支定界法的并行化，我们开发了实现可变计算粒度的并行化算法。在Beowulf集群中实现了BMI分支和定界算法。(4)在BMI优化的实数编码遗传算法中，引入了一种降阶的个体表达式和一种基于LMI优化的个体评价方法。所开发的方法使我们能够更准确地评估个人相比，传统的基于特征值的方法。(5)为了减少方法（4）的计算负担，我们还开发了一个充分利用Beowulf集群计算能力的并行化算法.基于BMI优化方法的同步优化研究（1）连杆-连杆系统由于其连杆结构的复杂性，是同步优化的最佳应用之一。并行链路系统的性能取决于控制器和链路结构。针对冗余并联系统，提出了一种基于LMI优化的最优功率分配控制方法。然而，尚未获得全局最优的链路结构和全局最优的控制行。(2)从实用的角度来看，建模和参数整定对于同步优化设计都很重要。在此背景下，我们开发了一种基于数据的控制器设计方法，基于非伪造控制技术和支持向量机。该方法阐明了基于数据的同时优化方法的可能性。

项目成果

期刊论文数量（0）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

PID Controller Design for Magnetic Levitation System based on Unfalsified Control Method with SVM

基于SVM非证伪控制方法的磁悬浮系统PID控制器设计

DOI：
发表时间：
2006
期刊：
影响因子：
0
作者：
Michihiro Kawanishi;Masanori Ukibune;Masaya Handa;Michihiro Kawanishi;浮舟正倫;Masanori Ukibune
通讯作者：
Masanori Ukibune

SVMを用いた非反証法に基づく磁気浮上システムのPID補償器設計

基于SVM不可证伪方法的磁悬浮系统PID补偿器设计

DOI：
发表时间：
2006
期刊：
影响因子：
0
作者：
Michihiro Kawanishi;Masanori Ukibune;Masaya Handa;Michihiro Kawanishi;浮舟正倫
通讯作者：
浮舟正倫

BMI Optimization by-using Parallel UNDX Real-coded Genetic Algorithm with Beowulf Cluster

基于Beowulf聚类的并行UNDX实数编码遗传算法的BMI优化

DOI：
发表时间：
2007
期刊：
Mechatronics, MEMS, and Smart Materials 6794
影响因子：
0
作者：
Michihiro Kawanishi;Masaya Handa;Michihiro Kawanishi;Michihiro Kawanishi;川西通裕;Michihiro Kawanishi
通讯作者：
Michihiro Kawanishi

Control System Design with Parallel Branch and Bound Method-a Novel Branching Operation and Variable Computational Granularity

并行分支定界法控制系统设计——一种新颖的分支运算和可变计算粒度