Second-order Transfer Function Model Research Articles

Pressure-driven dynamical microfluidic pumping system for droplet production

Compact and affordable microfluidic pumping is critical for point-of-care applications. Here we proposed a data driven dynamical system to build up a pressure-driven microfluidic pump with a small budget. Firstly, a precision flow sensor is required to obtain the dynamic flow rates as the responses to the driven pressures. Then the flow rate dataset under varying operation pressures is used for data training and model-based system identification. With a first-order or second-order transfer function model, the specifications of pressure-driven microfluidic pumping system are analyzed by the model-based system identification algorithm. Also, all the specifications including the gain, time constant, natural frequency, and damping ratio are updated online as new test data are introduced from more experimental trials. To perform a non-bulky design purpose, the data training system identification is taken on a commercial smartphone. Once the training performance is satisfied, the pressure-driven system could be operated without any flow sensors. The system is used for two-phase flow controls as a demonstration, showing a rapid response of pumping. Dynamic characteristics and the effects of flow resistance on the pumping performance are analyzed to verify its suitability for a wide range of microfluidic applications.

Dynamic Calibration of a Thin-Film Heat-Flux Sensor in Time and Frequency Domains.

This paper mainly studies the model design of a thin-film heat-flux sensor (TFHFS), and focuses on the comparison of three dynamic calibration methods. The primary motivation for studying this came from the urgent need for heat-flux dynamic measurements in extreme environments, and the one-sidedness of the dynamic performance evaluation of the corresponding TFHFS. The dynamic theoretical model of the TFHFS was originally established on the principle of a temperature gradient on the basis of a thermal radiation boundary. Then, a novel TFHFS sensor was developed, which can be used at temperatures above 880 °C and has a high sensitivity of 2.0 × 10−5 mV/(W/m2). It can function stably for long durations under a heat-flux density of 3 MW/m2. The steady-state, transient, and frequency calibration of a TFHFS were compared to comprehensively analyze the dynamic characteristics of the TFHFS. The steady-state response time measured by the step excitation method was found to be 0.978 s. The QR decomposition method was applied to the steady-state response experimental model construction, and the fitting degree of a second-order transfer function model obtained was 98.61%. Secondly, the transient response time of the TFHFS was 0.31 ms based on the pulse-excitation method. The transient relationship between the surface temperature and the heat flux, and the pulse-width dependence of the TFHFS transient response time were established. Surprisingly, the response frequency of the TFHFS, about 3000 Hz, was efficiently tested using the frequency response function (FRF), which benefitted from the harmonic characteristics of a periodic square-wave excitation signal. Finally, a comprehensive evaluation of the dynamic performance of the TFHFS was realized.

Monitoring Internal and External Load During Volleyball Competition.

The aim of this study was to identify the relationships between continuously measured internal and external load variables during volleyball competition. A total of 8 male elite volleyball athletes (Belgian Liga A and Liga B) were monitored during official competition matches. In total, 63 individual measurements are included in this study. The authors used heart-rate (HR) data as internal load and accelerometer-based activity as external load. Data were recorded at a sampling frequency of 1Hz using wearable technology during official competition. Workload during continuous game play and individual jumps performed while serving and spiking (selected by means of video analysis) were studied using correlation analysis and dynamic time-series modeling. Significant linear correlations were observed between peak acceleration and maximal HR of individual serves (ρ = .62; P = 1.6e-5) and spikes (ρ = .49; P = 1.2e-3) that were performed during the warm-up. These same actions performed during the match did not show significant correlations. The correlation between the mean HR and mean activity throughout the entire match was also found to be significant (ρ = .67; P = 2.0e-9). With respect to the time-series models, the mean value for the goodness of fit (RT2) between HR and activity was equal to .83 and .67 for the individual actions and the entire matches, respectively. The results show that there are strong relationships between internal and external load during volleyball competition. Second-order transfer function models are capable of explaining the main dynamics of HR (internal load) in response to accelerometer-based activity (external load). Time-series analysis of continuously measured workload is proposed for use in practice.

Dynamic performance of optimized microwave assisted extraction to obtain Eucalyptus essential oil: energy requirements and environmental impact

Abstract The dynamic performance of a microwave-assisted extraction (MAE) was studied during the extraction of eucalyptus essential oil. The effect of different process variables such as solid/liquid ratio (1:1, 1:3, or 1:5), stirring speed (0, 200, or 400 rpm), and power microwave output (360, 450, or 540 W) on obtained yield, energy requirements and environmental impact were assessed. The maximum yield was 1.26 ± 0.01% and the steam generation velocities between 4.8 and 8.8 g/min favor the extraction. In terms of environmental impact, the lowest EI99 value obtained was 6.93 ± 0.1 mPT/g. A multi-response optimization was performed to identify the operating conditions that maximize yield, while minimize energy requirements and environmental impact. Temperature dynamics and extraction kinetics were fitted to a second-order transfer function model, aimed to evaluate the role of heating patterns on the process performance. Finally, a controlled temperature experiment was carried out under the optimal conditions.

Model identification of critically damped second order plus time delay systems

ABSTRACTIn the present work, a simple method is proposed to calculate the parameters of a critically damped second-order transfer function model from the fractional step response of higher order systems. Five simulation examples are given to show the simplicity of the proposed method. The method makes use of a unique property of a critically damped second order plus time delay system (Harriott, Process Control, McGraw Hill, New Delhi), that, a time of 2.58τ is required to reach a fractional step response of 0.73. The time required to reach 0.35 (or any value) of fractional step response is also required. The derivation of the equations for the model parameters is simpler than that proposed by Rangaiah and Krishnaswamy (Ind. Engg. Chemistry Research, V 33, 1994, 1867–1871). The ISE and IAE values for the present method are compared with that of Rangaiah and Krishnaswamy. The method is also modified to get the model parameters of a FOPTD system: .

Study on the second-order transfer function models for dynamic tests of flat-plate solar collectors Part I: A proposed new model and a fitting methodology

The existing second-order transfer function models (TFMs) for solar collector dynamic tests are reviewed in light of the heat transfer principles, their inherent relationship, and limitations. Then, another form of TFM in terms of the collector heat removal factor FR is put forward in this study. And the equivalent relationships among different forms of TFMs are elucidated. Strict error analysis and the weighed least square (WLS) method are used to construct model coefficients in the TFMs due to random measurement errors of data points in dynamic tests. Accuracy levels of the three TFMs will be validated with experimental data in the companion paper (Deng et al., 2015).

Identification of Unstable Second-order Transfer Function Model with a Zero by Optimization Method

A technique is presented is to identify a transfer function of an unstable second-order plus time delay (SOPTD) with a zero. An optimization method is used to estimate the model parameters to match the closed loop responses. A method is given for the initial guess values of the model parameters (time delay, steady state gain and the values of poles and zero). The method is applied to three simulation examples. The presented method gives good results. The measurement noise and disturbance effects on the model identification are also reported.

Modelling the dynamics of expiratory airflow to describe chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is characterized by expiratory airflow limitation, but current diagnostic criteria only consider flow till the first second and are therefore strongly debated. We aimed to develop a data-based individualized model for flow decline and to explore the relationship between model parameters and COPD presence. A second-order transfer function model was chosen and the model parameters (namely the two poles and the steady state gain (SSG)) from 474 individuals were correlated with COPD presence. The capability of the model to predict disease presence was explored using 5 machine learning classifiers and tenfold cross-validation. Median (95% CI) poles in subjects without disease were 0.9868 (0.9858-0.9878) and 0.9333 (0.9256-0.9395), compared with 0.9929 (0.9925-0.9933) and 0.9082 (0.9004-0.9140) in subjects with COPD (p < 0.001 for both poles). A significant difference was also found when analysing the SSG, being lower in COPD group 3.8 (3.5-4.2) compared with 8.2 (7.8-8.7) in subjects without (p < 0.0001). A combination of all three parameters in a support vector machines corresponded with highest sensitivity of 85%, specificity of 98.1% and accuracy of 88.2% to COPD diagnosis. The forced expiration of COPD can be modelled by a second-order system which parameters identify most COPD cases. Our approach offers an additional tool in case FEV1/FVC ratio-based diagnosis is doubted.

Concept for the integration of geometric and servo dynamic errors for predicting volumetric errors in five-axis high-speed machine tools: an application on a XYC three-axis motion trajectory using programmed end point constraint measurements

A modelling approach for volumetric error prediction taking into account geometric and servo dynamic errors in a five-axis high-speed machine tool is proposed in this paper. Polynomial functions are used to represent and then predict the geometric errors. A simple second-order transfer function model is used to model and predict the servo dynamic error. The servo dynamic errors are added to the axis position geometric errors and propagated to the tool and workpiece using matrix transformations. The validity of the error integration concept is tested for a XYC three-axis motion trajectory. Two experimental setups are used. The first experimental test used the KGM grid encoder instrument to estimate the parameters of the servo dynamic error models of the X- and Y-axes. The second experimental test used a programmed end point constraint procedure with measurement of the 3D volumetric positioning errors between a point on the tool holder and another fixed to the machine table. The tests involve maintaining the nominal coincidence of these two points whilst exercising the three axes. These last tests are used to estimate the geometric error parameters and also to validate the prediction performance of the integrated geometric and dynamic model. The result shows the effectiveness of the error integration concept.

Simulation and modeling-SPICE2 voltage-programmable transfer function modeling

A general transfer function model with voltage-programmable coefficients is developed, from which first- and second-order transfer function models are derived. In these models, the voltage-programmable feature is achieved by making use of multiplier or product terms in the multidimensional polynomial controlled voltage sources provided in SPICE2 where, by definition, one variable in a product pair is the voltage analog of a coefficient value. The utility of the voltage-programmable transfer function models lies in their ability to simulate a multiple of transfer functions using only one or two subcircuits and cascade the models to represent more complicated transfer functions. An example application to the simulation of a motor speed regulator control system is described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>