Boli Chen

Robust Sinusoid Identification With Structured and Unstructured Measurement Uncertainties

In this note a globally stable methodology is proposed to estimate the frequency, phase, and amplitude of a sinusoidal signal affected by additive structured and bounded unstructured disturbances. The structured disturbances belong to the class of time-polynomial signals incorporating both bias and drift phenomena. Stability and robustness results are given by resorting to Input-to-State stability arguments. Simulation comparative results show the effectiveness of the proposed technique.

An Adaptive Observer-Based Switched Methodology for the Identification of a Perturbed Sinusoidal Signal: Theory and Experiments

This paper deals with a novel adaptive observer-based technique for estimating the amplitude, frequency, and phase of a single sinusoidal signal from a measurement affected by structured and unstructured disturbances. The structured disturbances are modeled as a time-polynomial so as to represent bias and drift phenomena typically present in applications, whereas the unstructured disturbances are modelled as bounded noise signals. The proposed estimation technique exploits a specific adaptive observer scheme equipped with a switching criterion allowing to properly address in a stable way poor excitation scenarios. The estimators stability properties are analyzed by input-to-state stability arguments. The practical characteristics of the proposed estimation approach are evaluated and compared with other existing tools by extensive simulation trials. Real experimental results are provided as well.

Robust parametric estimation of biased sinusoidal signals: A parallel pre-filtering approach

In this paper, a parallel pre-filtering scheme is presented to address the problem of estimating the parameters of a sinusoidal signal from biased and noisy measurements. Extending some recent result on pre-filtering-based frequency estimators, a parallel pre-filtering scheme is proposed to deal with the unknown offset and bounded measurement perturbations, which are typically present in several practical applications. A simple frequency estimator, having parallel second-order pre-filters, is introduced. The behaviour of the proposed algorithm with respect to bounded additive disturbances is characterized by Input-to-State Stability arguments. Numerical examples shows the effectiveness of the proposed technique.

Deadbeat kernel-based frequency estimation of a biased sinusoidal signal

This paper introduces a novel deadbeat frequency estimator for possibly biased noisy sinusoidal signals. The proposed estimation scheme is based on processing the measurements by Volterra integral operators with suitably designed kernels, that allow to obtain auxiliary signals not affected by the unknown initial conditions. These auxiliary signals are exploited to adapt the frequency estimate with a variable structure adaptation law that yields finite-time convergence of the estimation error. The worst case behavior of the proposed algorithm in the presence of bounded additive disturbances is characterized by Input-to-State Stability arguments. Numerical simulations are given to show the effectiveness of the proposed method and to compare it with some other techniques available in the recent literature.

A nonlinear adaptive observer with excitation-based switching

This paper presents a MIMO nonlinear adaptive observer, which is characterized by a robust excitation-based switching strategy. The proposed switching algorithm allows to address the scenario of poor excitation, while a conservative minimum duration of excitation interval for ensuring a progressive improvement is determined. The robustness of the devised method with respect to the bounded unstructured perturbation is studied by a input-to-state stability analysis. Simple simulation results show the effectiveness of the proposed technique.

Sinusoidal signal estimation from a noisy-biased measurement by an enhanced PLL with generalized error filtering

In this paper, an Enhanced Phase-Locked Loop (EPLL) architecture is proposed to deal with the problem of estimating the amplitude, the frequency and the phase of a sinusoidal signal from a noisy measurement. The EPLL scheme is chacterized by an error filter and a phase-feedforward term that are embedded in the estimation algorithm for improved noise rejection and transient performances. By designing the error filter and by selecting the parameters of the PLL according to the guidelines suggested by the stability proof, the technique addressed in the paper allows to cope with the presence of measurement bias while damping the effect of high-frequency noise and harmonics. Simulation comparisons show the effectiveness of the proposed estimation technique.

Robust finite-time estimation of biased sinusoidal signals

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 lawfed by the aforementioned auxiliary signalsis 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.

A Fast-Convergent Modulation Integral Observer for Online Detection of the Fundamental and Harmonics in Grid-Connected Power Electronics Systems

Harmonics detection is a critical element of active power filters. A previous review has shown that the recursive discrete Fourier transform and the instantaneous p-q theory are effective solutions to extracting power harmonics in single-phase and three-phase power systems, respectively. This paper presents the operating principle of a new modulation function integral observer algorithm that offers a fast solution for the extraction of the fundamental current and the total harmonic current when compared with existing methods. The proposed method can be applied to both single- and three-phase systems. The observer-based algorithm has an advantageous feature of being able to be tuned offline for a specific application, having fast convergence, and producing estimated fundamental component with high circularity. It has been tested with both simulations and practical experiments for extracting the total harmonic current in a highly efficient manner. The results have confirmed that the proposed tool offers a new and highly effective alternative for the smart grid industry.

The modulation integral observer for linear continuous-time systems

The paper deals with the design of a state observer for linear time-invariant systems, which converges in finite-time without resorting to high-gain injection. The devised observer is based on modulation integrals as the main enabling tool, and can be implemented as a jump-linear system. The dynamics of the state estimation error is proven to be input-to-state stable with respect to the additive measurement noise on the systems output. Numerical examples are included to show the effectiveness of the proposed method and to provide comparisons with some existing techniques.

Online Detection of Fundamental and Interharmonics in AC Mains for Parallel Operation of Multiple Grid-Connected Power Converters

Parallel operation of multiple grid-connected power converters through LCL filters is known to have the potential problem of triggering oscillations in the ac mains. Such oscillatory frequencies are not integral multiples of the fundamental frequency and, hence, form a new source of interharmonics. Early detection of such oscillations is essential for the parallel power converters to move out of the unstable zone. This paper presents an online observer-based algorithm that can perform fast detection of interharmonics within a specified frequency band. The algorithm has been adopted in a specific and reduced form from an integral observer algorithm for detection of fundamental and interharmonic voltage components in the ac mains. A new method based on the kernel signal for fast interharmonic detection is proposed and practically verified. It has been implemented in a digital controller to detect oscillations such as those occurring between two grid-connected power converters. The practical results indicate that the algorithm can locate such frequency within the specific frequency band within one mains cycle.