An adaptive “quasi” repetitive controller for the fundamental frequency estimation of periodic signals

Fedele, Giuseppe; Ferrise, Andrea; Muraca, P.

doi:10.3182/20140824-6-za-1003.00352

Cited by 5 publications

(1 citation statement)

References 36 publications

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“…From the control perspective, online estimation is the crucial field of interest. A large amount of algorithms have been proposed using adaptive and nonlinear filtering techniques [5], [6], [7] and adaptive observers [8], [9], [10]. All of these methods formally guarantee the global stability of the estimator.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation for a Sinusoidal Signal with a Time-Varying Amplitude

Chen

2022

2022 European Control Conference (ECC)

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This paper addresses the parameter estimation problem of a non-stationary sinusoidal signal with a timevarying amplitude, which is given by a known function of time multiplied by an unknown constant coefficient. A robust estimation algorithm is proposed for identifying the unknown frequency and the amplitude coefficient in real-time. The estimation algorithm is constructed based on the Volterra integral operator with suitably designed kernels and sliding mode adaptation laws. It is shown that the parameter estimation error converges to zero within an arbitrarily small finite time, and the robustness against bounded additive disturbances is certified by bounded-input-bounded-output arguments. The effectiveness of the estimation technique is evaluated and compared with other existing tools through numerical simulations.

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