故障条件下子空间预测控制的对偶分解

doi:10.3969/j.issn.0255-8297.2014.06.016

应用科学学报 ›› 2014, Vol. 32 ›› Issue (6): 652-660.doi: 10.3969/j.issn.0255-8297.2014.06.016

• 控制与系统 • 上一篇

故障条件下子空间预测控制的对偶分解

王建宏1，许莺1，熊朝华1，徐波2

1. 中国电子科技集团公司第二十八研究所，南京210007
2. 南京大学天文与空间科学院，南京210093

收稿日期:2013-11-24 修回日期:2014-05-12 出版日期:2014-11-28 发布日期:2014-05-12
作者简介:王建宏，博士，副教授，研究方向：系统辨识与凸优化，E-mail: wangjianhong3624@163.com
基金资助:
国家“863”高技术研究发展计划基金(No.2012SYAB321)资助

Dual Decomposition in Subspace Predictive Control under Fault Condition

WANG Jian-hong1, XU Ying1, XIONG Zhao-hua1, XU Bo2

1. The 28th Research Institute, China Electronics Technology Group Corporation, Nanjing 210007, China
2. College of Astronomy and Space Science, Nanjing University, Nanjing 210093, China

Received:2013-11-24 Revised:2014-05-12 Online:2014-11-28 Published:2014-05-12

摘要/Abstract

摘要： 研究故障条件下子空间预测控制器的设计问题，在推导输出预测估计值后分析残差矢量的统计分布特性
及残差矢量在各个瞬时时刻处的具体形式. 针对含有等式和不等式约束条件的预测控制器最优化问题，通过对偶
运算将较复杂的约束优化转化为无约束优化问题，采用最近邻梯度法即可求得基-对偶优化问题的最优解. 最后以
直升机悬停状态为例，验证控制器设计方法的有效性.

关键词: 故障, 子空间预测控制, 对偶分解, 规范项

Abstract: This paper studies design of controllers in subspace predictive control structure under faulty conditions.
Having derived the output predictive estimations, statistic distribution of the residual and the expression
are analyzed. To optimize the prediction controller with equalities and inequalities, dual decomposition is used
to convert the former constrained optimization into unconstrained optimization. The incremental proximal
method is applied to solve the primal-dual optimization problem. With a helicopter as an example, effectiveness
of the proposed control strategy is verified.

Key words: fault, subspace predictive control, dual decomposition, regularization term

中图分类号:

TP273

王建宏1，许莺1，熊朝华1，徐波2. 故障条件下子空间预测控制的对偶分解[J]. 应用科学学报, 2014, 32(6): 652-660.

WANG Jian-hong1, XU Ying1, XIONG Zhao-hua1, XU Bo2. Dual Decomposition in Subspace Predictive Control under Fault Condition[J]. Journal of Applied Sciences, 2014, 32(6): 652-660.

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故障条件下子空间预测控制的对偶分解

Dual Decomposition in Subspace Predictive Control under Fault Condition

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