Transfer Function Estimation Research Articles

Reliability of assessing postural control during seated balancing using a physical human-robot interaction

This study evaluated the within- and between-visit reliability of a seated balance test for quantifying trunk motor control using input–output data. Thirty healthy subjects performed a seated balance test under three conditions: eyes open (EO), eyes closed (EC), and eyes closed with vibration to the lumbar muscles (VIB). Each subject performed three trials of each condition on three different visits. The seated balance test utilized a torque-controlled robotic seat, which together with a sitting subject resulted in a physical human-robot interaction (pHRI) (two degrees-of-freedom with upper and lower body rotations). Subjects balanced the pHRI by controlling trunk rotation in response to pseudorandom torque perturbations applied to the seat in the coronal plane. Performance error was expressed as the root mean square (RMSE) of deviations from the upright position in the time domain and as the mean bandpass signal energy (Emb) in the frequency domain. Intra-class correlation coefficients (ICC) quantified the between-visit reliability of both RMSE and Emb. The empirical transfer function estimates (ETFE) from the perturbation input to each of the two rotational outputs were calculated. Coefficients of multiple correlation (CMC) quantified the within- and between-visit reliability of the averaged ETFE. ICCs of RMSE and Emb for all conditions were ≥0.84. The mean within- and between-visit CMCs were all ≥0.96 for the lower body rotation and ≥0.89 for the upper body rotation. Therefore, our seated balance test consisting of pHRI to assess coronal plane trunk motor control is reliable.

Optimal Enforcement of Causality in Non-Parametric Transfer Function Estimation

Traditionally, non-parametric impulse and frequency response functions are estimated by taking the ratio of power spectral density estimates. However, this approach may often lead to non-causal estimates. In this letter, we derive a closed form expression for the impulse response estimator by smoothed empirical transfer function estimate, which allows optimal enforcement of causality on non-parametric estimators based on spectral analysis. The new method is shown to be asymptotically unbiased and of minimum covariance in a positive semidefinite sense among a broad class of linear estimators. Numerical simulations illustrate the performance of the new estimator.

Central chemoreflex activation induces sympatho-excitation without altering static or dynamic baroreflex function in normal rats.

Central chemoreflex activation induces sympatho‐excitation. However, how central chemoreflex interacts with baroreflex function remains unknown. This study aimed to examine the impact of central chemoreflex on the dynamic as well as static baroreflex functions under open‐loop conditions. In 15 anesthetized, vagotomized Sprague‐Dawley rats, we isolated bilateral carotid sinuses and controlled intra‐sinus pressure (CSP). We then recorded sympathetic nerve activity (SNA) at the celiac ganglia, and activated central chemoreflex by a gas mixture containing various concentrations of CO 2. Under the baroreflex open‐loop condition (CSP = 100 mmHg), central chemoreflex activation linearly increased SNA and arterial pressure (AP). To examine the static baroreflex function, we increased CSP stepwise from 60 to 170 mmHg and measured steady‐state SNA responses to CSP (mechanoneural arc), and AP responses to SNA (neuromechanical arc). Central chemoreflex activation by inhaling 3% CO 2 significantly increased SNA irrespective of CSP, indicating resetting of the mechanoneural arc, but did not change the neuromechanical arc. As a result, central chemoreflex activation did not change baroreflex maximum total loop gain significantly (−1.29 ± 0.27 vs. −1.68 ± 0.74, N.S.). To examine the dynamic baroreflex function, we randomly perturbed CSP and estimated transfer functions from 0.01 to 1.0 Hz. The transfer function of the mechanoneural arc approximated a high‐pass filter, while those of the neuromechanical arc and total (CSP‐AP relationship) arcs approximated a low‐pass filter. In conclusion, central chemoreflex activation did not alter the transfer function of the mechanoneural, neuromechanical, or total arcs. Central chemoreflex modifies hemodynamics via sympatho‐excitation without compromising dynamic or static baroreflex AP buffering function.

An Approximate Transfer Function Model of Two Serially Connected Heterogeneous Transmission Lines

This brief presents an approximate transfer function model of two heterogeneous transmission lines connected in series. The proposed model is simple, intuitive, and can accurately describe the frequency response of various serially connected heterogeneous interconnects which satisfy a validity condition. The exact error of the proposed model is also provided. According to our analysis, the validity condition can be clearly interpreted by the propagation and the reflection waves. The accuracy of the proposed model is verified by comparing the calculated transfer function of LC-dominant off-chip and RC-dominant on-chip examples against SPICE simulation results. In these verifications, the maximum errors between calculation and simulation are, respectively, 2.58% and 3.32% for off-chip and on-chip examples. The computation time is also reduced about 29.76 and 289.07 times compared with a single-channel model and the SPICE ${w}$ -element model. With the proposed model, designers can easily understand the channel responses of diverse serially connected heterogeneous interconnects.

Interaction Analysis of Multivariate Control Systems Under Bayesian Framework

Detection and quantification of interactions between the loops of a multivariable system are of interest for different purposes, such as control system design, optimization, fault diagnosis, and performance assessment. This paper proposes a new method for interaction analysis based on decomposing the estimated transfer function between variables in the form of impulse response coefficients. The method not only provides an estimation of the direct (feedback and interaction free) transfer function between the variables, but also provides a measure of strength of all the indirect paths connecting variables together individually. The advantage of the method is that it provides a complete picture of the different paths through which variables can influence each other along with an estimation of the energy transferred through each path independently. The analysis is performed by estimating structural vector autoregressive models under Bayesian framework. Bayesian approach provides certain advantages in terms of dealing with high dimensional variables and overparameterization problem. An appropriate design of the prior probability for the model parameters also better ensures convergence to a physically interpretable model. A procedure to design the prior distribution for the model parameters is presented in this paper.

Transmission Line Modeling of Inclined Compressible Fluid Flows

Compressible fluid flow modeling for inclined lines is a challenging phenomenon due to the nonlinearity of the governing equations and the spatial–temporal dependency of the fluid density. In this paper, the transmission line analytical model is applied to the determination of inclined compressible fluid flow's dynamics. To establish this model, an exact transcendent solution is developed by solving the Navier–Stokes equation in the Laplace domain. A transfer function approximation, allowing the fluid flow transients determination, is recovered from the exact solution using residual calculations. The error resulting from the polynomial fraction approximation of the transfer functions is circumvented through frequency response corrections for the approximation to meet the exact function steady-state behavior. The effect of gravity and fluid compressibility on the fluid flow dynamics as well as the interplay between those two factors are illustrated through the pressure and flow rate's frequency and time responses.

Modal testing of hydraulic pipeline systems

Dynamic models of fluid power systems require accurate descriptions of hydraulic pipeline systems. For laminar flow in a rigid pipeline, modal approximations of transcendental transfer functions lead to a multi-degrees-of-freedom description. This suggests the application of experimental modal analysis to investigate fluid dynamics in hydraulic pipeline systems. The concept of modal testing is adapted accordingly and demonstrated for a straight pipeline, the same pipeline with a single side branch, and a pipeline system with three side branches. Frequency response functions are determined by injecting a defined flow rate excitation and measuring pressure responses along the pipelines. The underlying theory is confirmed by comparisons between calculated transcendental, measured, and estimated rational frequency response functions. Natural frequencies, damping ratios, and pressure mode shapes are identified. Although the experiments are made for low flow rates and stiff pipeline walls, they indicate the way to perform modal testing in practical applications of fluid power.

Transfer Function Estimation in System Identification Toolbox via Vector Fitting

This paper considers black- and grey-box continuous-time transfer function estimation from frequency response measurements. The first contribution is a bilinear mapping of the original problem from the imaginary axis onto the unit disk. This improves the numerics of the underlying Sanathanan-Koerner iterations and the more recent instrumental-variable iterations. Orthonormal rational basis functions on the unit disk are utilized. Each iteration step necessitates a minimal state-space realization with these basis functions. One such derivation is the second contribution. System identification with these basis functions yield zero-pole-gain models. The third contribution is an efficient method to express transfer function coefficient constraints in terms of the orthonormal rational basis functions. This allows for estimating transfer function models with arbitrary relative degrees (including improper models), along with other fixed and bounded parameter values. The algorithm is implemented in the tfest function in System Identification Toolbox (Release 2016b, for use with MATLAB) for frequency domain data. Two examples are presented to demonstrate the algorithm performance.

Analytical Models of High-Speed RLC Interconnect Delay for Complex and Real Poles

Continuous shrinking of the size of CMOS technology leads to extremely fast devices, but the resulting interconnect structures impose so many parasitic effects that the advantage of extremely scaled and ultrahigh-speed transistors would be completely overshadowed if appropriate remedial steps are not taken. This requires an accurate and efficient estimation of interconnect parasitics and analysis of their impact on integrated circuit performance. This paper proposes a new delay model for RLC interconnect networks in CMOS technology based on a second order approximate transfer function. The proposed modeling approach includes all possible scenarios (complex poles, real poles, and double poles) in the interconnect model. Simulation results show that the proposed delay model is almost independent of the ratio of ${V}_{\mathrm { {out}}} / V_{\mathrm { {in}}}$ , and the driver resistance has significant impact on the delay. The simulation results also show that the real pole model provides better accuracy and is much faster than the complex pole model. This observation would help to optimize the values of interconnect parasitics for faster operation.

TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study

Artificial Neural Networks (ANNs) are well known for their credible ability to capture non-linear trends in scientific data. However, the heuristic nature of estimation of parameters associated with ANNs has prevented their evolution into efficient surrogate models. Further, the dearth of optimal training size estimation algorithms for the data greedy ANNs resulted in their overfitting. Therefore, through this work, we aim to contribute a novel ANN building algorithm called TRANSFORM aimed at simultaneous and optimal estimation of ANN architecture, training size and transfer function. TRANSFORM is integrated with three standalone Sobol sampling based training size determination algorithms which incorporate the concepts of hypercube sampling and optimal space filling. TRANSFORM was used to construct ANN surrogates for a highly non-linear industrially validated continuous casting model from steel plant. Multiobjective optimization of casting model to ensure maximum productivity, maximum energy saving and minimum operational cost was performed by ANN assisted Non-dominated Sorting Genetic Algorithms (NSGA-II). The surrogate assisted optimization was found to be 13 times faster than conventional optimization, leading to its online implementation. Simple operator's rules were deciphered from the optimal solutions using Pareto front characterization and K-means clustering for optimal functioning of casting plant. Comprehensive studies on (a) computational time comparisons between proposed training size estimation algorithms and (b) predictability comparisons between constructed ANNs and state of art statistical models, Kriging Interpolators adds to the other highlights of this work. TRANSFORM takes physics based model as the only input and provides parsimonious ANNs as outputs, making it generic across all scientific domains.

Optimized Finite Element Method for Acoustic Scattering Analysis With Application to Head-Related Transfer Function Estimation

Obtaining head-related transfer functions (HRTFs) is a challenging task, in spite of its importance in localizing sound in a three-dimensional (3D) environment or improving the performance of hearing aids, among their various applications. In this paper, an optimized finite element method through adaptive dimension size based on wavelength (frequency) for acoustic scattering analyses using ansys is presented. Initial investigation of the validity of our method is conducted by simulating scattered sound field for a solid sphere exposed to a far-field plane sound wave at 100 (equally spaced in logarithmic scale) frequencies between 20 and 20 kHz. Comparison of the equivalent HRTF results between the two methods shows a maximum deviation of less than 0.6 dB between our method and the analytical solution depending on the angle of rotation of the sphere with respect to sound source.

Novel Centralized IMC-PID Controller Design for Multivariable Processes with Multiple Time Delays

In this paper, a novel centralized IMC (internal-model-control)-PID (proportion-integration-differentiation) controller is designed for multivariable processes with multiple time delays. To reduce the influence of time delays, the process model is divided into the minimum common time delay part and the remaining part. The IMC-PID controller, consisting of a full-matrix filter and a diagonal PID controller, is obtained based on the IMC principle. The full-matrix filter described as the inverse of the remaining part is too complex to compute. Hence, the Nyquist set is employed to describe the dynamics of the filter. The approximate transfer function matrix of the filter is calculated by complex curve fitting. Besides, to reduce the approximation error and obtain stable filter elements, a compensator is introduced. The rules of selecting compensator parameters are proposed for stable filter elements. Finally, the IMC-PID controller parameters are determined after comprehensively considering the performance a...

Analysis of the Measurement System and Optimization of the Measurement Procedure for Detection of Thermal Memory Effects by Photoacoustic Experiments

Experimental verification of thermal memory effects represents a challenge that is important from both fundamental and practical points of view. Recent theoretical studies suggest that the thermal memory effect should lead to thermal resonances in the modulation frequency characteristics of photoacoustic response. Therefore, studies of thermal resonances in photoacoustic response represent an alternative for detection of the thermal memory effect and measurement of thermal memory properties. Since the resonances were not observed, this paper analyzes standard measurement setups and shows that the experimental technique should be optimized to provide a better chance of detection of thermal memory effects by photoacoustic measurements. The results show that a proper selection of modulation frequencies and the knowledge of the approximate transfer function of the electronic part of the photoacoustic measurement system are prerequisites for detection of thermal resonances in the modulation frequency characteristics of photoacoustic response.

The Short-Run Relationship Between Real Effective Exchange Rate and Balance of Trade in China

This paper analyzes the short-run relationship between the real effective exchange rate and the balance of trade in China. We examined the causality between effective exchange rate and balance of trade with Granger-Causality test using the monthly data from January 1994 to August 2009. The test suggests that in the short run balance of trade causes a change in effective exchange rate but not vice versa. The uni-directional relationship between exchange rate and balance of trade compels the use of transfer function methodology. Transfer function estimation shows that a shock in balance of trade has a 3-4 month delayed effect on effective exchange rate in the short-run but this delayed effect dissipates in the long run.

Analysis of over-sampling based identification

In this work, firstly, an asymptotic variance expression is derived for the transfer function estimates in the over-sampling based identification scheme. Then the result is used to analyze the over-sampling scheme. The asymptotic variance expression says that the joint covariance matrix of the transfer function estimates is proportional to the “generalized” noise-to-signal ratio. It is an application of the result in Ljung (1985); and it covers both open-loop and closed-loop tests. Using the result, one can show that informativity of the closed-loop tests without external excitation can be attained by using the over-sampling scheme, but only when the output disturbance has high frequency content beyond the bandwidth of the plant. Moreover, when the output disturbance has high frequency content and when test signal is used, the result points out that the over-sampling scheme can increase model accuracy, and, it will outperform conventional method with anti-aliasing filtering. Numerical examples are used to illustrate the asymptotic variance expression and the analysis about over-sampling scheme of identification.

New northwest Pacific radiolarian data as a tool to estimate past sea surface and intermediate water temperatures

A new radiolarian data set for transfer function estimates of past sea surface temperature (SST) and intermediate water temperature was developed in this study for the northwestern Pacific Ocean covering a region from 1° to 50°N and 120° to 167°E. We analyzed 87 sediments surface samples, selected 30 species and/or species group found in shallow water for estimating past summer SST and 17 species and/or species group found in the intermediate water for estimating past intermediate water temperature. Since the intermediate water temperature changes greatly between 200 and 500 m, our estimates provide values at 500 m because temperatures are relatively stable between 500 and 1000 m. In this context, we estimated past summer SST and intermediate water (at ~500 m) temperature within an error margin of 0.9 and 1.2°C, respectively. A test of the accuracy of our transfer functions, conducted on core samples provided by IODP Expedition 346 Site U1429 in the northern East China Sea, showed that the reconstructed summer SSTs fluctuated between 17.2 and 26.5°C in selected late Pleistocene sequences. These temperatures corresponded to modern winter and summer SST, respectively, which highlights the ability of our new database to accurately reconstruct summer SST. The reconstructed intermediate water temperature fluctuates between 3 and 8°C, which corresponds to the observed temperature range at depths of ~500 m at high and midlatitudes, respectively.

Modeling the effect of tilting, passive leg exercise, and functional electrical stimulation on the human cardiovascular system.

Long periods of bed rest negatively affect the human body organs, notably the cardiovascular system. To avert these negative effects and promote functional recovery in patients dealing with prolonged bed rest, the goal is to mobilize them as early as possible while controlling and stabilizing their cardiovascular system. A robotic tilt table allows early mobilization by modulating body inclination, automated passive leg exercise, and the intensity of functional electrical stimulation applied to leg muscles (inputs). These inputs are used to control the cardiovascular variables heart rate (HR), and systolic and diastolic blood pressures (sBP, dBP) (outputs). To enhance the design of the closed-loop cardiovascular biofeedback controller, we investigated a subject-specific multi-input multi-output (MIMO) black-box model describing the relationship between the inputs and outputs. For identification of the linear part of the system, two popular linear model structures-the autoregressive model with exogenous input and the output error model-are examined and compared. The estimation algorithm is tested in simulation and then used in four study protocols with ten healthy participants to estimate transfer functions of HR, sBP and dBP to the inputs. The results show that only the HR transfer functions to inclination input can explain the variance in the data to a reasonable extent (on average 69.8%). As in the other input types, the responses are nonlinear; the models are either not reliable or explain only a negligible amount of the observed variance. Analysis of both, the nonlinearities and the occasionally occurring zero-crossings, is necessary before designing an appropriate MIMO controller for mobilization of bedridden patients.

Control structure design and dynamics modelling of the organic Rankine cycle system

In this paper, the control structure for the organic Rankine cycle (ORC) system is proposed. This control structure is derived by using the state space model of the overall ORC system. The state space model is obtained from nonlinear equations of elements of ORC which are given and described. Because ORC is a multiple-input and multiple-output (MIMO) process, a loop pairing with minimum interactions is needed to be determined to obtain the optimal control structure. To make the best loop pairing decisions and to analyse the interactions of ORC, the non-square relative gain array (NRGA) and dynamic non-square relative gain array (DNRGA) methods are used. Approximated transfer functions are derived from Bode diagrams which are given by using definitions of DNRGA method. These transfer functions are used to get the optimal parameters of the control structure. The proposed control structure uses proportional and integral (PI) linear controllers. A given control performance of the proposed control structure is shown and analysed in a simulation.

Linearization of Power Amplifier using the Modified Feed Forward Method

A modified circuit for improving linearization of power amplifier based on the model of the Feed Forward circuit amplifier is proposed. With the help of mathematical model for the single power amplifier, the circuit is simulated and a demonstrator is fabricated and measured complex Taylor series are used for modeling the power amplifier by the approximation of the amplitude transfer function and the level-dependence of the transmission-phase of the power amplifier. This can be understood as a simplified form of volterra series. In our proof of concept experiment, we verified the concept but also found that the adjustment of the circuit is critically dependent on the drive conditions and linearization is achieved only for a narrow range of drive power. The proposed circuit in compared with the conventional Feed Forward amplifier in addition a significant increase in efficiency, to minimize the power of the distortion signal 3IMD-products at high drive levels.

補助フィルタによる2次経路逆伝達関数推定を用いるPre-inverse型ANCシステム

補助フィルタによる2次経路逆伝達関数推定を用いるPre-inverse型ANCシステム