|
|||||
|
|
| 求解大规模线性时不变系统的最优H2模型降阶问题的共轭梯度法 | |
| 引用本文： | 曾泰山,鲁春元,陈剑.求解大规模线性时不变系统的最优H2模型降阶问题的共轭梯度法[J].中山大学学报(自然科学版),2011,50(2). |
| 作者姓名： | 曾泰山 鲁春元 陈剑 |
| 作者单位： | 1. 中山大学数学与计算科学学院,广东广州,510275 2. 广东药学院医药信息工程学院,广东广州,510006 3. 佛山科学技术学院数学系,广东佛山,528000 |
| 基金项目： | 国家自然科学基金资助项目，中山大学985项目专项基金 |
| 摘 要： | 针对最优H2模型降阶问题，提出了适合大规模多输入多输出系统的共轭梯度法。该方法仅需利用一阶导数信息，存储量少，计算复杂度低，且具有超线性收敛性。实验结果显示了算法的有效性。 |
| 关 键 词： | 模型降阶 共轭梯度法 Grassmann流形 线性时+不变系统 |
| 收稿时间： | 2010-04-30; |
A Conjugated Gradient Algorithm for Optimal H2 Model Reduction of Large Scale Dynamical Systems |
|
| ZENG Taishan,LU Chunyuan,CHEN Jian.A Conjugated Gradient Algorithm for Optimal H2 Model Reduction of Large Scale Dynamical Systems[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2011,50(2). | |
| Authors: | ZENG Taishan LU Chunyuan CHEN Jian |
| Institution: | (1School of Mathematics and Computational Science, Sun Yat sen University, Guangzhou 510275, China；2College of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou 510006,China;3Department of Mathematics, Foshan University, Foshan 528000,China) |
| Abstract: | A conjugated gradient algorithm with super linear convergence which is suitable for the optimal H2 model reduction of the multi input multi-output large scale dynamical systems is proposed. The proposed algorithm computes only first-order derivative of the cost function. It has low storage requirement and computational cost. Numerical example demonstrates the approximation accuracy and computational efficiency. |
| Keywords: | model reduction conjugated gradient method Grassmann manifold linear time invariant system |
| 本文献已被 万方数据 等数据库收录！ | |
| 点击此处可从《中山大学学报(自然科学版)》浏览原始摘要信息 | |
| 点击此处可从《中山大学学报(自然科学版)》下载免费的PDF全文 | |