A Study of Hierarchical Forgetting Factors Adjusting Scheme in Parameter Estimation

• Main Authors: Liu, Yun Yang, 劉永揚
• Other Authors: Hsiao, Chao yin
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/86038021558955259575

碩士 === 逢甲大學 === 機械工程研究所 === 84 === In is study, two hierarchical methods are investigated, one is for determining the optimal adaptive forgetting factor for the recursive least squares filter algorithm, the other is for constructing this factor adjusting hierarchical structure. It is required that for a given required resolution about the forgetting factor, the number of developed branches of the factor adjusting hierarchical structure should be minimized. For observation and comparison, three fading memory recursive least squares filtering algorithms are constructed. The first one is called the method of parallel exhausting search, in which 20 parallel filters are constructed, each has a different forgetting factor ranged from 0.05 to 1.0 with an increment of 0.05 at each time stage. The filter has best performance is chosen. The second one is the method of hierarchical search of this study. The third one called themethod of estimated optimal uses the forgtting factor determined by the estimated nonstationary to noise ratio. Essentially, the method of parallel exhausting search is optimal in nature, and the method of estimated optimal willprovide the optimal forgetting factor if the nonstationary to noise ratio has been correctly estimated. The method of hierarchical search can expect a similarresult as that of parallel exhausting search, but with much less computation requirement. Simulation results can support the above arguments.