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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sidman, Michael D. DeAngelis, Franco E. Verghese, George C. |
| Copyright Year | 1990 |
| Description | Author affiliation: Digital Equipment Corporation, Storage Systems Advanced Development Group, 301 Rockrimmon Blvd. MS: CXO1-1/P26, Colorado Springs, Colorado 80919 (Sidman, Michael D.) || Martin Marietta Corporation, IR&D D18-D Advanced Avionics, P.O. Box 179 MS: G1630, Denver, Colorado 80201 (DeAngelis, Franco E.) || Massachusetts Institute of Technology, EECS Department Room: 10-069, Cambridge, Massachusetts 02139 (Verghese, George C.) |
| Abstract | Gradient search methods that fit the parameters of a user-defined transfer function model to experimental Logarithmic frequency response data are presented. The methods match a model based on physically significant parameters, including natural frequencies of poles and zeroes and damping ratios of complex poles and zeroes. The algorithms construct and utilize their own analytical gradient descent functions, based on the desired model. One method attempts to fit both log magnitude and phase, while another identifies a minimum phase transfer function model from only log magnitude frequency response data. The performance of the log magnitude algorithm is shown to be superior to traditional methods using non-logarithmic frequency response data, including those used in commercially available frequency response analyzers. The algorithms are shown to perform well, especially for systems with lightly-damped dynamics. |
| Starting Page | 1888 |
| Ending Page | 1892 |
| File Size | 404712 |
| Page Count | 5 |
| File Format | |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1990-05-23 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | System identification Frequency response Transfer functions Algorithm design and analysis Performance analysis Dynamic range Noise level Signal to noise ratio Data storage systems Springs |
| Content Type | Text |
| Resource Type | Article |
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