Robust finite-time estimation of biased sinusoidal signals: A volterra operators approach

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• 作者：Gilberto Pin^a ; ^{gilbertopin@alice.it}Author Vitae ; Boli Chen^b ; ^{boli.chen10@imperial.ac.uk}Author Vitae ; Thomas Parisini^b ; ^c ; ^{t.parisini@gmail.com}Author Vitae
• 关键词：Finite-time estimation ; Sinusoidal parameters estimation ; Volterra operator ; Kernels
• 刊名：Automatica
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：77
• 期：Complete
• 页码：120-132
• 全文大小：1927 K
• 卷排序：77

文摘

A novel finite-time convergent estimation technique is proposed for identifying the amplitude, frequency and phase of a biased sinusoidal signal. Resorting to Volterra integral operators with suitably designed kernels, the measured signal is processed yielding a set of auxiliary signals in which the influence of the unknown initial conditions is removed. A second-order sliding mode-based adaptation law–fed by the aforementioned auxiliary signals–is designed for finite-time estimation of the frequency, amplitude, and phase. The worst case behavior of the proposed algorithm in presence of the bounded additive disturbances is fully characterized by Input-to-State Stability arguments. The effectiveness of the estimation technique is evaluated and compared with other existing tools via extensive numerical simulations.