基于不同遗忘因子的递推子空间辨识算法策略性能比较

详细信息

Performance Comparison of Recursive Subspace Identification Algorithms Based on Different Forgetting Factors

1.
Department of Automatic Control, The Second Artillery Engineering University, Xi'an 710025, China
2.
The 96115 PLA Troops, Tonghua 134008, China

摘要: 根据遗忘因子作用于数据的一般形式以及Hankel矩阵构造形式，导出在变遗忘因子作用下的Hankel矩阵无偏更新形式，并据此设计了新的变遗忘因子递推子空间辨识算法．分别从与无偏更新的Hankel矩阵接近程度、跟踪性能以及对距离信息的敏感性等方面比较了改进方法、固定遗忘因子方法以及传统的变遗忘因子方法的性能．仿真结果表明，改进算法具有更好的性能．
- 子空间辨识 /
- 递推算法 /
- 固定遗忘因子 /
- 变遗忘因子
Abstract: An unbiased update form of Hankel matrix is designed based on both the data form with forgetting factor and the construction of Hankel matrix. On this basis, a new recursive subspace identification algorithm with variable forgetting factor is proposed. The modified method, the fixed forgetting factor method and the traditional variable forgetting factor method are compared from the aspects of the approach degree to the unbiased update Hankel matrix, the performance in tracking system parameters and the distance sensitivity, etc. Simulation results show that the performance of the modified method is better than the others.
- subspace identification /
- recursive algorithm /
- fixed forgetting factor /
- variable forgetting factor