Robust Frequency Estimation Under Additive Symmetric α-Stable Gaussian Mixture Noise

Here the estimating problem of a single sinusoidal signal in the additive symmetricα-stable Gaussian(ASαSG)noise is investigated.The ASαSG noise here is expressed as the additive of a Gaussian noise and a symmetricα-stable distributed variable.As the probability density function(PDF)of the ASαSG is complicated,traditional estimators cannot provide optimum estimates.Based on the Metropolis-Hastings(M-H)sampling scheme,a robust frequency estimator is proposed for ASαSG noise.Moreover,to accelerate the convergence rate of the developed algorithm,a new criterion of reconstructing the proposal covar-iance is derived,whose main idea is updating the proposal variance using several previous samples drawn in each iteration.The approximation PDF of the ASαSG noise,which is referred to the weighted sum of a Voigt function and a Gaussian PDF,is also employed to reduce the computational complexity.The computer simulations show that the performance of our method is better than the maximum likelihood and the lp-norm estimators.

l_(1)-norm Based GWLP for Robust Frequency Estimation

In this work,we address the frequency estimation problem of a complex single-tone embedded in the heavy-tailed noise.With the use of the linear prediction(LP)property and l_(1)-norm minimization,a robust frequency estimator is developed.Since the proposed method employs the weighted l_(1)-norm on the LP errors,it can be regarded as an extension of the l_(1)-generalized weighted linear predictor.Computer simulations are conducted in the environment of α-stable noise,indicating the superiority of the proposed algorithm,in terms of its robust to outliers and nearly optimal estimation performance.

Robust generation of frequency combs in a microresonator with strong and narrowband loss

Octave-spanning frequency comb generation in microresonators is promising, but strong spectral losses caused by material absorption and mode coupling between two polarizations or mode families can be detrimental. We examine the impact of the spectral loss and propose robust comb generation with a loss of even 300 dB/cm.Cavity nonlinear dynamics show that a phase change associated with spectral losses can facilitate phase matching and Kerr comb generation. Given this unique capability, we propose a novel architecture of on-chip spectroscopy systems.

Effective Control of Smart Hybrid Power Systems:Cooperation of Robust LFC and Virtual Inertia Control Systems

A modern power system is expected to consist primarily of renewables,which either lack or have less rotating masses(i.e.,source of inertia)compared to the traditional generation sources.However,the growth of renewables generation,based on power electronics,can substantially decrease the inertia levels of renewable power grids,which can create several frequency stability issues,resulting in power system degradation.To address this issue,this paper presents a recent virtual inertia scheme predicated on electric vehicles(EVs)to mimic the necessary inertia power in low-inertia smart hybrid power systems(SHPSs),thus regulating the system frequency and avoiding system instability.Moreover,to guarantee robust performance and more stability for SHPSs against multiple perturbations,system uncertainties,and physical constraints,this paper also proposes a robust control strategy relying on a coefficient diagram method(CDM)for the load frequency control(LFC)of SHPSs considering high renewables penetration and EVs.The efficacy of the proposed system(i.e.,robust LFC with the proposed VIC strategy)is validated by comparison with a conventional LFC with/without the proposed VIC system.In addition,the simulation outcomes show that the proposed system can considerably support smart low-inertia hybrid power systems for many different contingencies.