A parallel prefiltering approach for the identification of a biased sinusoidal signal: Theory and experiments

Parisini

2017

Automatica

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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.

Section: Anf Techniques Represent An Effective Alternative To Handle mentioning

confidence: 99%

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

Parisini

2017

Automatica

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“…Abstracting from the aforementioned electrical and power systems applications, several solutions to the sinusoidal estimation problem outlined above have been conceived in the system-theoretic and signal processing fields, and many results are given in terms of adaptive observers (see [11], [12], [13], [14], [15], [16], [17] among others), or nonlinear adaptive systems [18], [19], [20]. Notably, all of these methods formally guarantee the global stability of the estimator.…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

Robust Frequency-Adaptive PLL with Lyapunov Stability Guarantees

2020 IEEE Conference on Control Technology and Applications (CCTA)

Fedele

et al. 2020

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The Global Quadrature Phase-Locked-Loop (GQ-PLL) is a recently-devised PLL-type architecture (based on Quadrature Signal Generation) able to track a biased sinusoidal signal with unknown frequency and amplitude. The original GQPLL formulation resorted to a non-standard nonnormalized adaptive law, able to guarantee the global convergence of the estimates for arbitrarily large adaptation gains, thus enabling arbitrarily fast adaptation transients. On the other side, the non-conventional adaptation law used in the original formulation makes it difficult to apply robustifying modifications of adaptive control. In this connection, the present work presents a new formulation for the PLL internal dynamics in order to obtain a convenient 1st order linear-in-the parameters error model, which can be dealt with by a conventional nonnormalized adaptive law, to which a robustifying modification such as projection can be applied. The large-gain global stability of the adaptive system is proven by Lyapunov arguments. The overall adaptive PLL is named Robustified GQPLL (RGQPLL).

“…Abstracting from the specific power-grid signal estimation problem, several solutions to the sinusoidal estimation problem outlined above have been conceived in the systemtheoretic and signal processing fields, and many results are given in terms of adaptive observers (see [13], [14], [15], [16], [17], [18], [19] among others), or nonlinear adaptive systems [20], [21], [22]. Notably, all of these methods formally guarantee the global stability of the estimator.…”

Section: Introductionmentioning

confidence: 99%

Globally-stable tracking and estimation for single-phase electrical signals with DC-offset rejection

IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society

Fedele

et al. 2019

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The present work introduces a new algorithm, named Global Quadrature PLL (GQPLL) for tracking a sinusoidal signal and for estimating its frequency and amplitude. The proposed technique derives from the well-known PLL architecture based on Quadrature Signal Generation (QSG), that is widely used for tracking the fundamental of single-phase electrical signals. The proposed algorithm improves the existent QSG-PLL solutions from two different perspectives. First, the cancellation of the DC-bias is embedded by construction. Moreover, a Lyapunov-based stability analysis guarantees the global convergence of the estimates for arbitrarily large adaptation gains, enabling fast adaptation transients. The provided simulations show that the algorithm is able to deal with sudden variations of the fundamental frequency and of the DC-bias magnitude.