Frequency Domain Identification Research Articles

A Möbius Transform Approach for Improved MIMO Frequency Domain Identification

To improve the numerical conditioning of a frequency domain subspace algorithm (FSID) when identifying continuous time transfer functions a general Mobius transformation can be employed. The Mobius transformation is a more general class of transformations which include the bilinear transformation as a special case. For the state-space model class of MIMO transfer functions we derive the relations describing how the state-space realization of a transfer function is converted under a Mobius transformation. With an extensive numerical example we illustrate that a particular choice of the Mobius transformation leads to transfer function estimates with, in general, significantly improved accuracy. Copyright (C) 2021 The Authors.

Parametric Identification of a Linear Time Invariant Model for a Subglottal System

Abstract Models of the human body are key in bio-engineering and medical applications. This study presents the identification, in time and frequency domains, of linear time invariant models of the human subglottal system, for the clinical assessment of vocal function. For time domain identification, the input-output data corresponds to the glottal volume velocity and the acceleration registered by a sensor on the neck skin of the patient. For frequency domain identification, the frequency response of the subglottal tract module is used. Maximum likelihood and prediction error methods are applied. Additionally, the Akaike and Bayes Information Criteria are used to select the models order.

FSID - A Frequency Weighted MIMO Frequency Domain Identification and Rational Matrix Approximation Method for Python, Julia and Matlab

An open source toolbox, FSID, implemented in the Python, Julia and MATLAB programming languages is described. The toolbox provides scripts which estimates linear multiinput multi-output state-space models from sample data using frequency-domain subspace algorithms. Algorithms which estimate models based on samples of the transfer function matrix as well as frequency domain input and output vectors are provided. The algorithms can be used for discrete-time models, continuous-time models as well as for approximation of rational matrices from samples corresponding to arbitrary points in the complex plane. The algorithms can handle frequency dependent weighting which enable to obtain approximate BLUE estimates. To reduce the computational complexity for the estimation algorithms, an accelerated algorithm is provided which evaluate the state-space realization of the transfer function matrix at arbitrary points.

Frequency-domain identification of stereoelectroencephalographic transfer functions for brain tissue classification

Abstract In drug-resistant epileptic patients, direct electrical brain stimulation sessions may be needed to identify epileptic regions on the brain before surgery. In this context, the classification of the brain tissue in which the electrodes are implanted in is very important for the interpretation of observed responses. This paper presents a new method for tissue classification based on the study of the baseline data with signal processing methods and features estimated from non parametric frequency identification of transfer functions. The method is tested on actual data and compared to visual classification of contacts co-registered on magnetic resonance imaging. The results show that good separability between matters, with up to 80% accuracy, can be achieved when considering the pairing of two consecutive electrodes.

Guidelines for generalised quantitative frequency domain design of optimised multi‐resonant AC current regulators for grid‐connected inverters

This study establishes a set of frequency-domain phase margin-oriented quantitative design guidelines for deriving coefficients of optimised multi-resonant AC current regulators, consisting of series-connected terms. Such an arrangement allows straightforward extension of existing design guidelines for developing coefficients of optimised single-resonant AC current regulators. Practical restrictions imposed by, relatively, low switching frequency are also considered, yielding corresponding design guidelines generalisation.

Optimized Design for a Device to Measure Thermal Contact Conductance During Friction Stir Welding

Friction stir welding (FSW) is a solid-state welding process that is finding increasing use in a variety of industries, owing to its ability to create high-quality welds with less heat input than fusion welding. While the modeling of FSW has been an active effort for at least 15 years, two input parameters, namely the friction coefficient and the heat transfer coefficient, are still adjustable quantities that are difficult to measure. This lack of information compromises the predictive capability of FSW models. While the modeling of friction between the tool and workpiece remains a complex task, the measurement of heat transfer should be possible, but has not been adequately addressed because of the difficulty of accessing the relevant interface with thermocouples. This paper presents a multi-layered frequency-domain thermoreflectance (FDTR) method and transducer design to measure the heat transfer coefficient between the spinning tool and the workpiece. Due to constraints of the welding process, a multi-layered structure is needed for a useable measurement to maximize the heat flow from the modulated heating surface through the heat transfer interface into the welded workpiece. An analytical 2D thermal quadrupole model is shown to be useful in determining layer properties. A multi-layered structure for a specific tool design is validated using COMSOL and optimized. This process can be used to determine the ideal transducer structure to maximize the signal from an FDTR measurement during a friction stir welding process.

Frequency-Domain Identification Based on Pseudorandom Sequences in Analysis and Control of DC Power Distribution Systems: A Review

Frequency-domain identification based on wideband techniques has become a popular method in the analysis and control of various dc power distribution systems. In the method, a single converter or a system is perturbed by an external wideband voltage or current injection, the resulting voltage or current responses are measured, and Fourier analysis is applied to extract the spectral information of the measured variables. Most often, the system or converter input and output impedances and the loop gain are the quantities of interest. One class of perturbation signals, pseudorandom binary sequences, has become widely used because most of such signals can be generated using simple shift-register circuitry. As the signals are deterministic and binary, they are well suited to perform measurements on power-converter systems in real time, allowing fast response to system variations through, for example, adaptive controllers. This article reviews the pseudorandom binary sequences applied to dc power distribution systems and discusses their advantages as well as limitations. The conventional maximum-length binary sequence, inverse-repeat binary sequence, discrete-interval binary sequence, and orthogonal binary sequences are considered. Several experimental results from various dc power systems are presented and used to demonstrate the applicability of the discussed methods.

An Innovative Aerial Manipulator with Tandem Ducted Fans: Modeling, Control, and Simulation

This paper proposes an innovative ducted fan aerial manipulator, which is particularly suitable for the tasks in confined environment, where traditional multirotors and helicopters would be inaccessible. The dynamic model of the aerial manipulator is established by comprehensive mechanism and parametric frequency-domain identification. On this basis, a composite controller of the aerial platform is proposed. A basic static robust controller is designed via H-infinity synthesis to achieve basic performance, and an adaptive auxiliary loop is designed to estimate and compensate for the effect acting on the vehicle from the manipulator. The computer simulation analyses show good stability of the aerial vehicle under the manipulator motion and good tracking performance of the manipulator end effector, which verify the feasibility of the proposed aerial manipulator design and the effectiveness of the proposed controller, indicating that the system can meet the requirements of high precision operation tasks well.

A gain scheduling approach to improve pressure control in water distribution networks

Real time pressure control is a common technique adopted to face the problem of leakage reduction in water distribution networks. Recently, in the context of Water 4.0, the spread of wired water distribution networks has opened new possibilities in terms of sensing and communication, resulting in the possibility of adopting higher sampling rates and consequently higher closed-loop bandwidths for the control system. While this could be exploited to improve the performance, it has also drawn the attention of the fundamental question of closed-loop stability, which was seldom considered in a systematic way, especially in the hydraulic community. This works aims to combine some recent results in term of design of frequency domain controllers with a gain scheduling approach, to account and compensate for the main nonlinearities affecting the system under control, and to preserve stability and robustness of the closed-loop in a wide operating region. The approach is validated by means of simulated experiments performed on a detailed dynamic model of the water distribution network. In addition, the gain scheduling approach can improve the overall performance of the control scheme and allows avoiding heavy retuning of the regulator when applied to the nonlinear system.

Numerical and Experimental Investigation on Dynamic Characteristic Changes of Encased Steel Profile Before and After Cyclic Loading Tests

This paper presents a numerical and experimental investigation regarding changes in dynamic characteristics (natural frequencies, mode shapes, and damping ratios) of encased steel profile of concrete-encased composite column-steel beam connections prior to and following lateral cyclic loading tests. To do so, four specimens with different column-beam connection details were considered. Pre-ambient vibration measurements were first conducted to extract experimental dynamic characteristics of encased steel profile in column-beam connections using enhanced frequency domain decomposition (EFDD) method in frequency domain and stochastic subspace identification (SSI) method in time-domain. Next, encased steel columns were enforced with longitudinal rebar, stirrups, and concrete to turn them into concrete-encased composite column. Lateral cyclic loading tests were performed on composite column-beam connections until failure. Concrete, stirrups, and rebar were removed and cleaned from the encased steel column after the cyclic loading tests. Post-ambient vibration measurements were repeated on the damaged models for further evaluation and comparisons. Additionally, 3D finite-element models of the samples were constituted using Abaqus program, and modal analyses were performed for each specimen to obtain the numerical dynamic characteristics and compare them with experimental results. The results show that natural frequencies distinctly decrease due to damages in the column-beam connection zones. The maximum decreases were calculated as 8.53% and 16.01% in EPCSB-I; 6.92% and 16.44% in EPCSB-II; 17.38% and 12.20% in EPCSB-III; as well as 23.10% and 22.85% in EPCSB-IV for EFDD and SSI methods, respectively. Also, after the cyclic loading tests, increasing of flexibility and rotational movements due to the decrease in joint stiffness has affected the mode shapes. When the initial finite-element analyses and experimental results were compared with each other, the maximum differences were obtained between 0.18% and 8.99% for EPCSB-I, 2.62% and 25.27% for EPCSB-II, 0.84% and 28.60% for EPCSB-III, and 0.19% and 29.87% for EPCSB-IV, respectively.

Delay-compensated control of sandwiched ODE–PDE–ODE hyperbolic systems for oil drilling and disaster relief

Motivated by engineering applications of subsea installation by deepwater construction vessels in oil drilling, and of aid delivery by unmanned aerial vehicles in disaster relief, we develop output-feedback boundary control of heterodirectional coupled hyperbolic PDEs sandwiched between two ODEs, where the measurement is the output state of one ODE and suffers a time delay. After rewriting the time-delay dynamics as a transport PDE of which the left boundary connects with the sandwiched system, a state observer is built to estimate the states of the overall system of ODE-heterodirectional coupled hyperbolic PDEs–ODE–transport PDE using the right boundary state of the last transport PDE. An observer-based output-feedback controller acting at the first ODE is designed to stabilize the overall system using backstepping transformations and frequency-domain designs. The exponential stability results of the closed-loop system, boundedness and exponential convergence of the control input are proved. The obtained theoretical result is applied to control of a deepwater oil drilling construction vessel as a simulation case, where the simulation results show the proposed control design reduces cable oscillations and places the oil drilling equipment to be installed in the target area on the sea floor. Performance deterioration under extreme and unmodeled disturbances is also illustrated.

Multilayer thermal object identification in frequency domain using IR thermography and vector fitting

SummaryThis paper deals with the identification of the thermal parameters of multilayer objects using the concept of thermal impedance. In order to perform such identification, temperature evolution in time is obtained by an infrared camera after power excitation is applied in the investigated structure. Infrared thermography offers the advantage of being a noncontact temperature detection and measurement method. In many practical cases, it is impossible to use contact temperature measurements. Typically, the power in the form of a step function is applied. In order to calculate the thermal impedance of an object, temperature and power are converted into the frequency domain using the Laplace transform for s = jω. Then, the poles of the thermal impedance are identified using vector fitting, which allows calculating the thermal impedance as a sum of partial fractions. This corresponds directly to the Foster network of a thermal object. In addition, the vector fitting method offers much better convergence in comparison with other methods using the polynomial rational approximation of thermal impedance. A considerable improvement of the numerical Laplace transform in high frequency range is proposed. In this approach, the variable s = jω is replaced by , and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.

Frequency domain identification using adaptive Fourier decomposition method with polynomials

The adaptive Fourier decomposition method is an approximation technique of generalised Fourier series, it leads to fast approximations by selecting basis functions in a maximal selection criterion. In recent research studies, it has been efficiently applied in the identification of linear time-invariant systems and a new algorithm is named two-step (T-S) algorithm. In this work, some further modification is made for the T-S algorithm. The improvement is made at the first step, where polynomials are used instead of cauchy integral formula. By doing this, the algorithm becomes simpler and easier to realise. The approximation errors are analysed. Owing to the analysed results, this new T-S algorithm is only to get poles for the finite rational orthogonal basis functions but not the approximation to the systems, the coefficients are estimated by using least-squares methods. The effectiveness is examined through numerical examples that show it takes much less running times and can get comparable approximating results. Besides, the case that errors are included in the frequencies is also studied, the obtained results imply that minor errors in the frequencies would not affect the estimation.

Identifying fiscal inflation in India: some recent evidence from an asymmetric approach

Purpose Among the many factors fueling the inflationary tendencies in an economy such as monetary shocks, structural shocks, demand shocks, external shocks and demographic changes, the issue of inflation (INF) has also been found to be related to fiscal policy decisions of the government. The purpose of this study is to investigate the inflationary tendencies in India particularly from the fiscal point of view. The study also examines the influence of other potential determinants such as output growth rate, interest rate, trade-openness (TO) and oil price inflation (OPI). Design/methodology/approach To examine the dynamic nature of association between fiscal deficit and inflation, the study applies the Toda-Yamamoto (1995) test and Breitung and Candelon (2006) test to investigate the nature of causality in time and frequency domain frameworks. In addition, to scrutinize the possibility of a long-run association, that too from an asymmetric point of view, the study applies a Non-linear Autoregressive Distributed lag model (NARDL) given by Shin et al. (2014). Finally, non-linear cumulative dynamic multipliers are used to trace the traverse between disequilibrium position of short-run and subsequent long-run equilibrium of the system. Findings The authors found a unidirectional causality from fiscal deficit to inflation in case of time domain analysis and no feedback causality is reported. However, in case of frequency domain design, causality from fiscal deficit to inflation is found at low frequencies only, i.e. no short-run causality is established and hence dynamic nature of the relationship between the two variables is vindicated. Using NARDL model, the results document the existence of an asymmetric long-run direct association between fiscal deficit and inflation. However, an increase in deficit is found to be more inflationary and a decrease affects the inflation with a lower magnitude. The asymmetric impact of fiscal deficit on inflation can be explained through the existence of liquidity constraints, consumption-investment downward inflexibility and the downward price stickiness. Contractionary monetary policy action is found to be more effective than an expansionary one, signifying the asymmetric influence of monetary policy actions on the inflation of India. Similarly, in a supply-constrained economy with downward price rigidity, the authors found an asymmetric impact of output growth and output decline on inflation. As regard to the trade-openness, although an asymmetry is reported, the signs refute the validation of Romer (1993) hypothesis. Finally, the impact of oil price inflation on the inflationary pressures is according to theory but the coefficients are devoid of statistical significance. Practical implications These results indicate some important policy recommendations. Fiscal consolidation strategy should be executed in an appreciable manner to achieve the sound fiscal health and lower INF. The disciplined fiscal strategy would also be imperative for an effective monetary policy. Monetary authorities should possess noticeable credibility to manage the macroeconomic system and policy stances should be implemented according to requirements of the economy. Growth in output should be encouraged to have two-fold benefits to the economy – reducing INF on the one hand and fiscal deficits on the other. Originality/value The study contributes to the existing literature in the following ways. First, taking note of dynamic nature of the relationship between these two variables, the study examined the deficit INF nexus in a dynamic and asymmetric framework. The novelty of the study is ensured by the very nature of it is the first study in case of India to identify the fiscal INF in an asymmetric configuration. The authors applied a NARDL model, given by Shin et al. (2014) to examine the existence of any cointegrating relationship in an asymmetric paradigm. Second, the nature of causality between fiscal deficit and INF has been examined in a time domain and FD framework to portray precisely the casual interactions between these two variables in the short-run and long run. The study will, therefore, enrich the existing literature along the asymmetric lines.

Frequency domain subspace identification of fractional order systems using time domain data with outliers

AbstractThis paper focuses on the identification of the multiple‐input multiple‐output commensurate fractional order systems. Different from the assumption of known frequency domain data and prior information about noise in the general frequency domain identification algorithm, the reliable frequency domain data is measured in this paper by designing special excitation signals. Then, in order to suppress the impact of noise, the data used in algorithm are truncated from the low frequency band. In addition, this paper considers the case where the sampling data are disturbed by outliers, and a matrix decomposition method with threshold value is developed to eliminate the influence of outliers. After that, the parameters of the system to be identified are estimated by the frequency domain subspace identification method. The validity of the proposed method is demonstrated by an illustrative numerical example.

Frequency Domain Design Method of Wavelet Basis Based on Pulsar Signal

During pulsar navigation, the high-frequency noise carried by the pulsar profile signal reduces the accuracy of the pulse TOA (Time of Arrival) estimation. At present, the main method to remove signal noise by using wavelet transform is to redesign the function of the threshold and level of wavelet transform. However, the signal-to-noise ratio and other indicators of the filtered signal need to be further optimised, so a more appropriate wavelet basis needs to be designed. This paper proposes a wavelet basis design method based on frequency domain analysis to improve the denoising effect of pulsar signals. This method first analyses the pulsar contour signal in the frequency domain and then designs a Crab pulsar wavelet basis (CPn, where n represents the wavelet basis length) based on its frequency domain characteristics. In order to improve the real-time performance of the algorithm, a wavelet lifting scheme is implemented. Through simulation, this method analyses the pulsar contour signal data at home and abroad. Results show the signal-to-noise ratio can be increased by 4 dB, the mean square error is reduced by 61% and the peak error is reduced by 45%. Therefore, this method has better filtering effect.

Very large amplitude vibrations of flexible structures: Experimental identification and validation of a quadratic drag damping model

This article presents a theoretical, numerical and experimental study of resonant structures undergoing very large amplitude vibrations. The purpose of this work is to validate a model for the damping due to the action of the air on a structure’s single-mode response in the steady-state. Experiments are performed on cantilever beams and beam assemblies of various sizes, from centimetric to micrometric, under harmonic base excitation. Dimensionless linear and nonlinear modal damping coefficients are simultaneously identified by means of frequency-domain identification techniques. These measurements demonstrate the pertinence of the presented model.

A Neural Network based Frequency-domain Design Method for the Optimal Fractional Order PI λ D μ Controller

A neural network (NN) based frequency-domain design method for the optimal PI λ D μ controller is proposed in this paper, dividing the tuning process of the PI λ D μ controller into two steps: the fractional orders of the controller are estimated by the NN based estimation models, and other controller parameters are calculated analytically using a modified frequency-domain method. A practical application of the proposed method on the permanent magnet synchronous motor (PMSM) speed control problem is studied. Motor speed control simulation is performed to verify the gain robustness, step response performance and anti-load disturbance performance of the obtained control system. Comparison with the typical frequency-domain method is performed and then the advantage of the proposed method is demonstrated.

Data-Driven Distributed Combined Primary and Secondary Control in Microgrids

This brief paper presents a comprehensive data-driven distributed combined primary/secondary controller design method for microgrids. This method provides transient and steady-state performances, including power sharing and voltage and frequency restoration while guaranteeing stability for fixed communication delays. Measured data are directly used for controller design, and no knowledge of the model structure or the physical parameters of the grid is required. Moreover, no assumption is made on the X/R ratio of the feeders. All control specifications are formulated as frequency-domain constraints on the two-norm of weighted sensitivity functions. Then, using a recently developed frequency-domain robust control design method, a distributed fixed-structure controller is synthesized in one step. The performance of the obtained controller is validated using hardware-in-the-loop (HIL) experiments. The results show considerable improvement in transient performance while providing power sharing and voltage and frequency restoration with a distributed implementation.

Design and Software Implementation of Analog and Digital Filters For Coherent Receivers under Noisy Channels

One of the most important stations in any communications system is the filtering station. Due to the noise power that effects on the signal, the system must include filtering process to eliminate this effect. In this paper, analog and digital filters are designed and implemented using Matlab tools to solve the problems occurred during receiving the signal that effects on the synchronization such as those for coherent receivers. The offsets of Phase and frequency are major problems in the identification of signals that results reduction in the performance; such as, whenever higher order modulations are used. Two systems are designed and simulated. The first one is analog system and the second one is digital system. 3rd order Butterworth filter is selected for system one and digital IIR filter is selected for system two. Filter order was selected according to diagnosis the level of noise power and the transmitted frequency to meet certain frequency domain design specifications. Obtained results showed excellent performance in the receiving and demodulating the received signal. Evaluation of the results is basically depend on comparison between the transmitted and received samples.