Showing papers on "Transfer function published in 2022"

Modified Equivalent-Input-Disturbance Approach to Improving Disturbance-Rejection Performance

Abstract: This article presents a modified equivalent-input-disturbance (MEID) approach that actively rejects exogenous disturbances. A dynamic compensator is newly introduced in a conventional equivalent-input-disturbance (EID) estimator to further suppress the disturbances. The mechanism of the MEID approach to improving disturbance rejection is analyzed based on the transfer characteristic from the EID to the output of the system, and a stability condition of the MEID control system is presented and is used to design the parameters of the system. A comparison with the conventional EID approach and the disturbance-observer method through experiments demonstrates the validity of the presented method.

Novel binary differential evolution algorithm based on Taper-shaped transfer functions for binary optimization problems

Abstract: In order to efficiently solve the binary optimization problems by using differential evolution (DE), a class of new transfer functions, Taper-shaped transfer function, is firstly proposed by using power functions. Then, the novel binary differential evolution algorithm based on Taper-shaped transfer functions (T-NBDE) is proposed. T-NBDE transforms a real vector representing the individual encoding into a binary vector by using the Taper-shaped transfer function, which is suitable for solving binary optimization problems. For verifying the practicability of Taper-shaped transfer functions and the excellent performance of T-NBDE, T-NBDE is firstly compared with binary DE based on S-shaped, U-shaped and V-shaped transfer functions, respectively. Subsequently, it is compared with the state-of-the-art algorithms for solving the knapsack problem with a single continuous variable (KPC) and the uncapacitated facility location problem (UFLP). The comparison results show that Taper-shaped transfer functions are competitive than existing transfer functions, and T-NBDE is more effective than existing algorithms for solving KPC problem and UFLP problem.

Power Dynamic Decoupling Control of Grid-Forming Converter in Stiff Grid

Abstract: This article proposes a grid-forming based decoupling approach, which effectively mitigates the dynamic interactions between active and reactive power, especially suitable for system stabilization in ultrastrong grids with short-circuit ratio over 30. The physical coupling behaviors are first revealed by analytical studies, where two potential resonances, respectively, located in 40–50 Hz and 0–10 Hz are discovered with mathematical proofs. Based on the results, the decoupling controller is then designed with transfer function approximation for practical usage. The control method not only suppresses the couplings but also cancels two pairs of conjugate poles through decoupling paths. Thanks to the cancellation, the stability margin is remarkably increased in stiff grids, and therefore, a significant bandwidth boost on the power synchronization control can be realized if desired. The experimental results are finally performed to verify the proposed decoupling method.

Modified Equivalent-Input-Disturbance Approach to Improving Disturbance-Rejection Performance

Abstract: This article presents a modified equivalent-input-disturbance (MEID) approach that actively rejects exogenous disturbances. A dynamic compensator is newly introduced in a conventional equivalent-input-disturbance (EID) estimator to further suppress the disturbances. The mechanism of the MEID approach to improving disturbance rejection is analyzed based on the transfer characteristic from the EID to the output of the system, and a stability condition of the MEID control system is presented and is used to design the parameters of the system. A comparison with the conventional EID approach and the disturbance-observer method through experiments demonstrates the validity of the presented method.

A Full-Feedforward Technique to Mitigate the Grid Distortion Effect on Parallel Grid-Tied Inverters

Abstract: In this article, a novel full-feedforward (FF) technique is introduced to lessen the effect of grid voltage distortion on injected current from the multiparallel grid-tied inverters. In this technique, the feedforward transfer function is applied to only one of the system inverters known as the target inverter. Hence, the investment cost for designing and implementing the FF technique is remarkably reduced. The proposed technique is based on introducing a virtual negative admittance at the target inverter to cancel the total parallel admittance of the system. Moreover, the reasons and conditions of instability, caused by the conventional FF techniques, are fully explored in this article. Then, by modifying the conventional FF techniques, a feedforward transfer function is proposed, which guarantees the strong dynamic performance of the system. Ultimately, an additional solution is devised to ensure a desirable grid voltage harmonic rejection ability of the proposed FF technique. Simulation and experimental results verify the validity of the proposed FF technique for a system consisting of two identical parallel grid-tied inverters.

Parameterized Modeling Incorporating MOR-Based Rational Transfer Functions With Neural Networks for Microwave Components

Abstract: Neuro-transfer function (neuro-TF) methods are deemed as powerful tools in modeling the electromagnetic (EM) behavior of microwave passive components. Existing neuro-TF methods either endure the issue of “order-changing” or the issue of mismatch of poles/zeros, both calling for specific algorithms to process the data of the transfer function coefficients as a part of model development. This letter proposes a novel neuro-TF method to eliminate the two issues simultaneously by using combined neural networks and model-order reduction (MOR)-based rational transfer functions. In the proposed method, the coefficients of the transfer function are computed by the MOR technique instead of vector fitting. The use of MOR allows the order of the transfer function to remain constant in different regions in the design parameter space, thereby avoiding the issue of “order-changing.” Additionally, the coefficients of the rational transfer function resultant from MOR are naturally sorted according to the order of frequency, which eliminates the issue of mismatch of poles/zeros and subsequently improves modeling accuracy. Compared with existing neuro-TF methods, the proposed method achieves better modeling accuracy for the same geometrical variations. Two microwave examples are utilized to demonstrate the advantages of the proposed method.

BMPA-TVSinV: A Binary Marine Predators Algorithm using time-varying sine and V-shaped transfer functions for wrapper-based feature selection

Abstract: The feature selection problem is one of the pre-processing mechanisms to find the optimal subset of features from a dataset. The search space of the problem will exponentially grow when the number of features increases. Hence, the feature selection problem is classified as an NP-hard problem, and exact algorithms cannot find the optimal subset at a reasonable time. As a result, approximate algorithms like meta-heuristic algorithms are extensively applied to solve the problem. The feature selection problem is a discrete (binary) optimization problem; consequently, a discrete meta-algorithm can be employed to find the optimal subset of features. One of the recently introduced meta-heuristic algorithms is Marine Predator Algorithm (MPA), which has shown good solutions to many continuous optimization problems. In this study, a novel Binary Marine Predator Algorithm using Time-Varying Sine and V-shaped transfer functions (BMPA-TVSinV) is proposed to find the optimal subset of features in datasets. The proposed algorithm applies two new time-varying transfer functions to convert the continuous search space to the binary one. These transfer functions considerably improve the performance of BMPA-TVSinV. Several well-known datasets with high-dimensional features and three coronavirus disease (COVID-19) datasets have been selected to compare the results of BMPA-TVSinV with some recently introduced binary meta-heuristic algorithms for the feature selection problem. The results show the superiority of BMPA-TVSinV in achieving high classification accuracy and feature reduction rate. The source code of BMPA-TVSinV for feature selection problem is publicly available at https://www.mathworks.com/matlabcentral/fileexchange/115315-bmpa-tvsinv-a-binary-metaheuristic-for-feature-selection . • A Binary Marine Predator Algorithm (BMPA-TVSinV) is proposed for feature selection. • Two novel time-varying Sine and V-shaped transfer functions are applied in BMPA. • The proposed algorithm is evaluated by high-dimensional and COVID-19 datasets. • BMPA-TVSinV archives a higher accuracy and feature reduction rate on datasets.

Recursive SISO Impedance Modeling of Single-Phase Voltage Source Rectifiers

Abstract: Due to the nonlinear time-periodic nature, precise impedance modeling of power-converter-based single-phase ac systems is complex. Small-signal modeling for the systems with a fixed operating point is easy, but the extension of the same procedure to the systems with time-periodic trajectory is still challenging. In this article, a recursive single-input single-output (SISO) impedance modeling framework for single-phase rectifiers is presented, which can greatly simplify both the modeling procedure and the resulting impedance model. A general linear-time periodic modeling method is proposed by extending the linear-time invariant modeling method, where frequency-coupling effects are modeled by the transfer function vector rather than the transfer function matrix, so the modeling complexity is reduced. Furthermore, based on the idea of mathematical induction, an analytical and accurate recursive SISO impedance model is derived. The resulting recursive SISO impedance model can characterize the frequency-coupling dynamics of arbitrary order with a low computation burden. Experiments validate the accuracy of the recursive SISO impedance modeling method.

Accurate Loop Gain Modeling of Digitally Controlled Buck Converters

Abstract: For the digitally controlled buck converters, the nonlinearity and time periodicity, caused by the pulsewidth modulator (PWM) and sample and hold, make the accurate frequency-domain analysis intractable. In this article, based on the harmonic transfer function (HTF) approach, a precise small-signal continuous-time modeling for the digitally controlled Buck converter operating in continuous-conduction mode (CCM) under constant-frequency voltage-mode control is presented. The sideband components on the closed-loop control are embedded in the model. Thus, this model is accurate within the full frequency domain region, which breaks the limit of Nyquist frequency. Furthermore, by overcoming the barrier of infinite series introduced by the sideband effects, the analytical loop gain expression is derived, which contributes to accurate stability assessment and reduction of computation burden. In addition, the proposed exact small-signal model has explained the reasons why different information injection points lead to different measured loop gains. Simulations and experimental results are conducted to verify the effectiveness of the proposed method.

A robust fractional-order controller design with gain and phase margin specifications based on delayed Bode's ideal transfer function

Abstract: In this study, a robust fractional-order controller design methodology for a type of fractional-order or integer-order model with dead time is proposed using phase and gain margin specifications. The delayed Bode’s ideal transfer function is used as a reference model to design the controller analytically. The delay term in delayed Bode’s ideal transfer function provides the exact determination of these frequency domain specifications when the system owns a dead time. The analytical robust controller design problem is transformed to solving four nonlinear equations with four unknown variables, two of which are the desired specifications; namely, phase and gain margins. The remaining two are the phase and gain cross-over frequencies. Next, some conditions are set based on the desired specifications so that nonlinear equations provide a unique solution . The proposed method is compared with the other existing robust controller methods based on the same frequency domain specifications. The simulation results reveal that the proposed method outperforms the other methods and also gives closer outcomes to the desired specifications.

High-Frequency Current Transformer Design and Construction Guide

Abstract: High-frequency current transformers (HFCTs) are well suited as sensors for measuring transient current signals on power cables, such as partial discharges (PD). If the HFCT is well designed and its measurement bandwidth matches the bandwidth of the signal to be measured, high sensitivities can be achieved. However, optimizing the HFCT design for a specific measurement bandwidth is a difficult task because various design parameters affect its transfer function. In addition, there is little helpful literature on the relationships between HFCT design and resulting sensitivity/bandwidth. To give guidance and fill this research gap, this article aims to provide all the necessary information on HFCT development. For this purpose, an analytical HFCT model is derived and validated with measurements from various self-made HFCT sensors. The method for measuring their transfer function (or transfer impedance) is presented and the measurement data of all our manufactured prototypes are given. Based on these data, valuable relationships between various design parameters and the HFCT transfer function are analyzed. Based on our experience, detailed information about the sensor manufacturing process is provided. The developed HFCT model is an effective tool to simulate and optimize the sensor transfer function before it is built. In this way, HFCT sensors can be designed quickly and cost-effectively specifically as required.

Wiener–Hammerstein nonlinear system identification using spectral analysis

Abstract: In this paper, a new approach is developed for the identification of Wiener–Hammerstein model structures. Unlike several other papers, the transfer functions of linear elements are of unknown structure. Indeed, the linear subsystems are not necessarily parametric or FIR. Furthermore, the function of nonlinear block can be nonparametric and noninvertible. The main challenge in identifying a Wiener–Hammerstein system lies in the separation of the dynamics over the input and the output LTI elements. Presently, this issue does not arise, without any conditions being imposed on the frequency band. Then, a two‐stage identification method is suggested. Firstly, the system is excited by a set of constant inputs to capture the system nonlinearity. In the second stage, an identification approach based on the spectral analysis and using periodic input signals is developed to determine the linear elements parameters. In the present method, very interesting concepts are used, like the Fourier decomposition, the frequency approach and the spectrum analysis. Simulations demonstrate that the proposed identification method is both effective and efficient.

The 21st Century Systems: An Updated Vision of Continuous-Time Fractional Models

Abstract: This paper presents the continuous-time fractional linear systems and their main properties. Two particular classes of models are introduced: the fractional autoregressive-moving average type and the tempered linear system. For both classes, the computations of the impulse response, transfer function, and frequency response are discussed. It is shown that such systems can have integer and fractional components. From the integer component we deduce the stability. The fractional order component is always stable. The initial-condition problem is analyzed and it is verified that it depends on the structure of the system. For a correct definition and backward compatibility with classic systems, suitable fractional derivatives are also introduced. The Grünwald-Letnikov and Liouville derivatives, as well as the corresponding tempered versions, are formulated.

Focused Laser Differential Interferometric Investigation of Turbulent Jet Spectra

Abstract: In this work, a model of focused laser differential interferometry (FLDI) is derived by incorporating the local intensity of each beam in an FLDI beam pair. We rederive some known transfer functions to reduce FLDI data. Additional transfer functions are also derived, intended to model increasingly complex disturbance fields, namely, isotropic turbulence. The new transfer functions account for disturbances not only in the streamwise direction but also in the two spanwise directions. Additionally, it is shown that strategically selecting the integration limits for the idealizedFLDIinthedenominatorofthetransferfunctions( d ϕ ∕ d x )cansimplifytheFLDIdata-reductionprocedure. This is done for disturbance fields in a finite boundary (e.g

Vibration Separation Methodology Compensated by Time-Varying Transfer Function for Fault Diagnosis of Non-Hunting Tooth Planetary Gearbox

Abstract: Due to planetary movement of planet gears, the vibration signal perceived by a stationary sensor is modulated and difficult to diagnose. This paper proposed a vibration separation methodology compensated by a time-varying transfer function (TVTF-VS), which is a further development of the vibration separation (VS) method in the diagnosis of non-hunting tooth planetary gearboxes. On the basis of VS, multi-teeth VS is proposed to extract and synthesize the meshing signal of a planet gear using a single transducer. Considering the movement regularity of a planetary gearbox, the time-varying transfer function (TVTF) is represented by a generalized expression. The TVTF is constructed using a segment of healthy signal and an evaluation indicator is established to optimize the parameters of the TVTF. The constructed TVTF is applied to overcome the amplitude modulation effect and highlight fault characteristics. After that, experiments with baseline, pitting, and compound localized faults planet gears were conducted on a non-hunting tooth planetary gearbox test rig, respectively. The results demonstrate that incipient failure on a planet gear can be detected effectively, and relative location of the local faults can be determined accurately.

Small-Signal Model of an Inductive Power Transfer System Using LCC–LCC Compensation

Abstract: The LCC–LCC compensation is widely used in the inductive power transfer systems. However, there is no simple and accurate small-signal equivalent circuit model for this resonant converter. Based on the extended describing function method, this article proposed a full-order (17th-order) equivalent circuit model to accurately predict the small-signal behaviors. For simplification, the full-order model is gradually simplified to a ninth-order model and finally to a fifth-order model. The input to output transfer function are analytically derived for the first time. Both simulation and experimental results are presented to justify the effectiveness of the model, and the model is accurate up to one-fifth of the switching frequency.

Compact Dual-Band and Wideband Filters With Resonant Apertures in Rectangular Waveguide

Abstract: The objective of this article is to describe a new family of microwave bandpass filters in the rectangular waveguide based on resonant apertures, which can be used to implement both single- and dual-band transfer functions. The use of capacitive stubs and a staircase configuration is also discussed in order to enhance the out-of-band response and the selectivity of the filter with respect to the state of the art. Finally, simulations are compared with measured results, showing very good agreement, thereby fully validating both the new filter topologies and the design procedure.

Modular Multilevel Converter Impedance Computation Based on Periodic Small-Signal Analysis and Vector Fitting

Abstract: Instability and oscillation issues originating in high-voltage direct current (HVDC) systems comprising modular multilevel converters (MMCs) are gaining increasing interest in the research community. To detect such phenomena in advance, considerable effort has been devoted recently to developing MMC models for small-signal analysis. The derivation of such models is a challenging task due to the topology and complex control structure of MMCs, which results in them having a multi-frequency response. To address this issue, scholars developed methods based on dynamic phasors and harmonic state-space modelling, which, however, require extensive pen-and-paper computations. In this paper, the periodic small-signal analysis (PAC) is adopted to determine numerically several MMCs transfer functions. Such functions can be computed between any electrical circuit node or input/output port, without the need to recast the three-phase average MMC model to derive a linear equivalent one, possibly in the DQ-frame. We show how vector fitting allows converting these functions to equivalent algebraic representations, which can be profitably used to design MMCs and study their stability following some parameter changes. To showcase this feature, we exploit one of these transfer functions to detect DC-side instability in a point-to-point HVDC system.