| Autor: |
Dongjin Lee, Arvind Balijepalli, Thomas W. LeBrun, Jason J. Gorman, Cedric Gagnon |
| Rok vydání: |
2005 |
| Předmět: |
|
| Zdroj: |
SPIE Proceedings. |
| ISSN: |
0277-786X |
| DOI: |
10.1117/12.615339 |
| Popis: |
System identification methods are presented for the estimation of the characteristic frequency of an optically trapped particle. These methods are more amenable to automated on-line measurements and are believed to be less prone to erroneous results compared to techniques based on thermal noise analysis. Optical tweezers have been shown to be an effective tool in measuring the complex interactions of micro-scale particles with piconewton resolution. However, the accuracy of the measurements depends heavily on knowledge of the trap stiffness and the viscous drag coefficient for the trapped particle. The most commonly referenced approach to measuring the trap stiffness is the power spectrum method, which provides the characteristic frequency for the trap based on the roll-off of the frequency response of a trapped particle excited by thermal fluctuations. However, the reliance on thermal fluctuations to excite the trapping dynamics results in a large degree of uncertainty in the estimated characteristic frequency. These issues are addressed by two parameter estimation methods which can be implemented on-line for fast trap characterization. The first is a frequency domain system identification approach which combines swept-sine frequency testing with a least-squares transfer function fitting algorithm. The second is a recursive least-squares parameter estimation scheme. The algorithms and results from simulation studies are discussed in detail. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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