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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liu Hsu Ortega, R. Damm, G. |
| Copyright Year | 1997 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. Fed. do Rio de Janeiro, Brazil (Liu Hsu) |
| Abstract | Online estimation of the frequency of a sinusoidal signal is a classical problem in systems theory that has many practical applications. In this paper we provide a solution to the long-standing fundamental open problem of ensuring a globally convergent estimation. More specifically, we propose a new adaptive notch filter whose dynamic equations exhibit the following remarkable features: (i) all signals are globally bounded and the estimated frequency is asymptotically correct for all initial conditions and all frequency values; (ii) we obtain a simple tuning procedure for the estimator design parameters, which trades-off the adaptation tracking capabilities with noise sensitivity, ensuring (exponential) stability of the desired orbit; (iii) transient performance is considerably enhanced, even for small and large frequencies, as witnessed by extensive simulations. To reveal some of the stability-instability mechanisms of the existing algorithms and motivate our modifications we make appeal to a novel nonlinear (state-dependent) time scaling. The main advantage of working in the new time scale is that we remove the coupling,between the parameter update law and the filter itself, decomposing the system into a feedback form where the required modifications to ensure stability become apparent. |
| Starting Page | 252 |
| Ending Page | 257 |
| File Size | 504076 |
| Page Count | 6 |
| File Format | |
| ISBN | 078034247X |
| DOI | 10.1109/COC.1997.631337 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1997-08-27 |
| Publisher Place | Russia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Frequency estimation Equations Tuning Asymptotic stability Magnetic noise Adaptive filters Parameter estimation Signal design Feedback Amplitude estimation |
| Content Type | Text |
| Resource Type | Article |
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