An Adaptive-Observer-Based Robust Estimator of Multi-sinusoidal Signals

Chen, Boli; Pin, Gilberto; Ng, Wai Man; Hui, S. Y. Ron; Parisini, Thomas

doi:10.1109/tac.2017.2752007

Cited by 20 publications

(11 citation statements)

References 37 publications

(62 reference statements)

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“…The bound (19) in Corollary 2 implies that if a fault f [l] in the form of f k [l] = c N,l k N −1 affects the system, the steady-state fault estimation error of the l-th fault, i.e., lim k→∞fk [l], is bounded as…”

Section: Polynomial Faultsmentioning

confidence: 99%

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Trade‐offs on fault estimation via proportional multiple‐integral and multiple‐resonant observers for discrete‐time systems

Sales-Setién¹,

Peñarrocha-Alós²

2019

IET Control Theory & Applications

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We develop a fault estimation strategy which is based on a novel proportional multiple-integral and multiple-resonant observer. This observer is an extension of the well-known PMI observer and it is able to estimate from low to high-frequency fault signals. The proposed estimation strategy is applied to discretetime systems which are affected by faults and stochastic noises. We present a multiobjective design strategy of the observer that fixes the trade-offs between practical engineering parameters regarding the noise attenuation and the ability to track each kind of fault dynamics considered by the augmented observer. We study the influence of the order of the observer on the steady-state and transient performance of the estimation of different types of faults. Finally, a numerical example is given to illustrate the effectiveness of the proposed observer, design and characterization.

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Section: Polynomial Faultsmentioning

confidence: 99%

“…Usually, the fast Fourier transform (FFT) is preferred in stationary conditions. For the estimation of sinusoidal signals with time‐varying amplitudes and frequencies different kinds of adaptive techniques, as the ones presented in [19, 20], are commonly utilised.…”

Section: Introductionmentioning

confidence: 99%

Trade‐offs on fault estimation via proportional multiple‐integral and multiple‐resonant observers for discrete‐time systems

Sales-Setién¹,

Peñarrocha-Alós²

2019

IET Control Theory & Applications

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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

Chen

Fedele

et al. 2020

2020 IEEE Conference on Control Technology and Applications (CCTA)

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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).

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“…The advanced results for multi-sinusoidal signals in continuous-time provide global exponential convergence [14], [15] and finite-time convergence [16]. Another interesting observer-based method is described in [17], where the number of sinusoids in the measurable signal is supposed to be time-varying.…”

Section: Introductionmentioning

confidence: 99%

Frequency Estimation of Multi-Sinusoidal Signals in Finite-Time

Vediakova,

Vedyakov,

Pyrkin

et al. 2020

Preprint

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This paper considers the problem of frequency estimation for a multi-sinusoidal signal consisting of n sinuses in finite-time. The parameterization approach based on applying delay operators to a measurable signal is used. The result is the nth order linear regression model with n parameters, which depends on the signals frequencies. We propose to use Dynamic Regressor Extension and Mixing method to replace nth order regression model with n first-order regression models. Then the standard gradient descent method is used to estimate separately for each the regression model parameter. On the next step using algebraic equations finite-time frequency estimate is found. The described method does not require measuring or calculating derivatives of the input signal, and uses only the signal measurement. The efficiency of the proposed approach is demonstrated through the set of numerical simulations.

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An Adaptive-Observer-Based Robust Estimator of Multi-sinusoidal Signals

Cited by 20 publications

References 37 publications

Trade‐offs on fault estimation via proportional multiple‐integral and multiple‐resonant observers for discrete‐time systems

Trade‐offs on fault estimation via proportional multiple‐integral and multiple‐resonant observers for discrete‐time systems

Robust Frequency-Adaptive PLL with Lyapunov Stability Guarantees

Frequency Estimation of Multi-Sinusoidal Signals in Finite-Time

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