Transfer Function Model Research Articles

Impact of Discrete-Time Modeling on Dual Input Buck-SEPIC Converter

This paper addresses aspects of a two-input Buck-SEPIC dc-dc converter. This integrated DC-DC converter processes power from two sources, two switches, and four different energy storage elements. The designed converter is processing 48 volts from two sources Vg1 = 36 V and Vg2 = 60 V. The transfer function modeling of this converter plays an important role in addressing several crucial aspects like optimal parameter design, controller design, stability, and robustness issues. Here, two types of transfer function modeling aspects are considered: continuous-time and discrete-time. The discrete-time transfer function is derived by considering trailing-edge as well as leading-edge digital pulse-width modulation scheme (DPWM) and for each of these cases time-delays in the control loop are also included. The designed converter parameters L1, L2, C1, and C2 are based on the design equations. The transfer functions are obtained in continuous-time and discrete-time for the TI-BS converter in the MATLAB environment. The experimental validation of the TI-BS dc-dc converter is performed through Hardware in Loop (HIL) using the real-time environment of the OPAL RT. For TIBS converter polezero configurations and frequency response characteristics are plotted. Using these plots important characteristics related to the deviation in phase angle of frequency response at higher frequencies due to RHP zeros are observed. The simulation studies are performed considering a 36 V / 60 V to 48 V, 500 W, prototype, DC power distribution system. The detailed modeling aspects in continuous-time as well as in discrete time are discussed considering a two-input Buck-SEPIC converter. The mathematical derivations of four different transfer function matrices using discrete-time modeling (trailing-edge and leading-edge modulation) are discussed in detail along with timing diagrams considering interval-1 and interval-2 sampling. The frequency response of the TI-BS dc-dc converter is affected when it is modeled using the discrete-time models and such frequency response deviation in phase response is observed for the TI-BS converter. The nonminimum phase response of this converter is shown using the Bode frequency response in the MATLAB environment and verified using the pole-zero map.

An adaptive fractional order controller design: A realization for liquid level regulation in liquid level plant

In this paper, an adaptive FO − IλD1−λ controller design is proposed using a frequency domain approach. The proposed adaptive controller parameters are tuned based on the frequency domain specifications. To realize the velocity error constant for the proposed controller, Oustaloup Recursive Approximation (ORA) method is employed. The proposed controller is realized for liquid level regulation in the Liquid Level Plant (LLP). An identification technique is proposed to identify a linear adaptable parameter transfer function (LAPTF) model of LLP. The performance of the proposed controller is compared with the existing works. It is observed that the proposed controller outperforms the existing controllers in the literature.

Looking beyond vaccines: Cultural tightness-looseness moderates the relationship between immunization coverage and disease prevention vigilance.

Advancements in vaccination technologies mitigate disease transmission risks but may inadvertently suppress the behavioral immune system, an evolved disease avoidance mechanism. Applying behavioral immune system theory and utilizing robust big data analytics, we examined associations between rising vaccination coverage and government policies, public mobility, and online information seeking regarding disease precautions. We tested whether cultural tightness-looseness moderates the relationship between mass immunization and disease prevention vigilance. Comprehensive time series analyses were conducted using American data (Study 1) and international data (Study 2), employing transfer function modeling, cross-correlation function analysis, and meta-regression analysis. Across both the US and global analyses, as vaccination rates rose over time, government COVID-19 restrictions significantly relaxed, community mobility increased, and online searches for prevention information declined. The relationship between higher vaccination rates and lower disease prevention vigilance was stronger in culturally looser contexts. Results provide initial evidence that mass immunization may be associated with attenuated sensitivity and enhanced flexibility of disease avoidance psychology and actions. However, cultural tightness-looseness significantly moderates this relationship, with tighter cultures displaying sustained vigilance amidst immunization upticks. These findings offer valuable perspectives to inform nuanced policymaking and public health strategies that balance prudent precautions against undue alarm when expanding vaccine coverage worldwide.

Vehicle seat surface real-time control system with linear actuator to reduce vertical impact

For regular vehicles, the vibration generated when a vehicle passes through a groove or step is dampened but still remains and causes whole-body vibration (WBV) to occupants through vehicle seat. Several epidemiological studies have clearly demonstrated that prolonged exposure to vibration from vehicles is detrimental to human health and may cause motion sickness. To reduce this whole-body vibration. We designed a simple and effective feed-forward control system with compact actuator compatible to the limited under-seat dimension and power outlet of compact general passenger cars and successfully authenticated the possibility of vertical vibration reduction by controlling the vehicle seat surface vertical displacement. In this research, we designed a real-time feed-forward control system with transfer function model estimation. This real-time control system contains a commercial DSP device providing coherence input and output with a controllable delay. With the application of transfer function model and state space model, this system successfully estimated the upcoming vibration acceleration according to the input of the vibrational acceleration time-domain data acquired from lower arm when the test vehicle passing a step. Furthermore, it is possible to process the input data and control the linear actuator precisely to reduce the vertical impact observed as setting force reduction.

Linear switched system modelling and analysis for the servo system

AbstractAiming at resolving the parameter uncertainty of the servo system under multi‐working conditions, a flatness‐based switched linear system model is proposed. Firstly, a fifth‐order linear switched discrete‐time system with uncertain parameters is established. The flatness properties of switched system is described and a de Bruijn's graph‐based framework is introduced for graphical description of the switched system. In addition, non‐linear bode diagrams are obtained via sweeping signals with multiple amplitudes. The discrete equations of the electromechanical servo system are established by the bode plots. The unknown parameters of the subsystems in switched model are identified by the simulated annealing algorithm, and compared with the least squares method to verify the accuracy of the identified parameters. Finally, the simulation model and experimental platform are constructed to verify the effectiveness of the proposed method. The switched model is compared with the classical transfer function model and single subsystems. The results indicate that the resolution of parameter uncertainty in servo systems is effective. The accuracy of the established switched model is about 99.5%. The accuracy of the switched linear system model of the electromechanical servo system is verified and the proposed modelling method is validated.

Design of an Electronically Controlled Fertilization System for an Air-Assisted Side-Deep Fertilization Machine

The traditional air-assisted side-deep fertilization device has some problems, such as inaccurate control system parameters and poor precision in variable fertilization. It seriously affects the application and popularization of the device. Aiming at the above problems, this paper wanted to realize the precise fertilizer discharge control of an air-assisted side-deep fertilization device. This paper designs an electronically controlled fertilization system based on a PID controller from the past. The system model was constructed in MATLAB, and the mathematical model and transfer function model of a stepper motor, the mathematical model of fertilizer discharge, and the stepper motor rotational speed were established too. In order to improve the accuracy of precise fertilizer discharge control system parameters, the system parameters were optimized based on the particle swarm optimization algorithm and the control system tuner toolbox. We had established a validation test platform to test the performance of a precise fertilizer discharge control system. In the actual experiment, the maximum stability coefficient of variation was 0.91% at the target fertilizer discharge mass level of 350 g/min, and the maximum error of fertilizer discharge was 4.14% at 550 g/min of the target fertilizer discharge mass level. By analyzing the test results of the precise fertilizer discharge control system, the new precise fertilizer discharge control system had good fertilizer discharge stability and could also meet the technical specification for quality evaluation of fertilization machinery (NY/T 1003-2006). This research can improve the fertilizer discharge accuracy of the air-assisted side-deep fertilization control system.

Study on a performance matching method of wind rotor and generator based on energy transfer.

Wind power systems are a promising form of energy supply. At present, most of the studies focuses on the performance of individual components such as wind rotors or generators, and the overall output effect of wind power system is determined by the characteristics of wind rotor and generator and their combined characteristics. However, the evaluation of the overall output characteristics of the system is rarely considered. In order to investigate the overall output of the system quickly, a performance matching method of wind rotor and generator based on energy transfer is proposed in this paper. Based on the series operating characteristics of the wind power system model, the energy transformation process of the wind rotor, generator and the whole system are unified described by energy transfer. On the premise that the performance of wind rotor and generator is known, the transfer function model of each component is established, and on this basis, the transfer function model of the overall system is obtained. Then, the overall output effect of the system is analyzed and evaluated by this system transfer function model. The performance of the model is analyzed and compared by using a vertical axis wind power system coupling test bench and MATLAB/Simulink software. The results show that the error between the system output based on the theoretical model and the wind tunnel test is less than 6.5%, and the trend of the simulation and the test curve of the system output is consistent. Therefore, this method can be used to quickly predict the overall output performance of the wind turbine and generator on the premise that the performance of each component is known, without the need to connect each component to a wind power system for testing.

Automated Data–Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function

This research focuses on the evolving dynamics of the power grid, where traditional synchronous generators are being replaced by non-synchronous power electronic converter (PEC)-interfaced renewable energy sources. The non-linear dynamics must be accurately modeled to ensure the stability of future converter-dominated power systems (CDPS). However, obtaining comprehensive dynamic models becomes more complex and computationally intensive as the system grows. This study proposes a scalable and automated data-driven partitioned modeling framework for CDPS dynamics. The method constructs reduced-ordered dynamic linear transfer function models using input-output measurements from a PEC switching model. Validation experiments were conducted on single-house and multi-house scenarios, demonstrating high accuracy (over 97%) and significant computational speed improvements (6.5 times faster) compared to comprehensive models. This framework and modeling approach offer valuable insights for efficient analysis of power system dynamics, aiding in planning, operation, and dispatch.

Near-field modeling of the head-related transfer function by using the dummy head sound source

Various approaches based on direct measurement have been used to obtain the precise headrelated transfer function (HRTF). However, several problems persist, such as scattering of sound source and distance effect, which are related to the measurement configuration. In this work, the modified dummy head having two sound sources located at the ear positions is applied as the sound source reciprocally to overcome the trouble. By using the near-field acoustic holography, the sound sources located in the ear holes are reconstructed from the measured data in the near-field hologram. One can predict the acoustic transfer function between the ear holes and the field positions at any point using the recovered source information described in spherical harmonics. The obtained transfer function is valid for predicting the binaural response from any sound source position. This configuration is possible to measure the near-field response with the relatively small scattering effect because of the low Helmholtz number of microphones. The far-field reconstruction of HRTF is also possible with the near-field measurement data using acoustical holography. The proposed method is demonstrated with the modified B&K HATS system, in which the microphones in the ear holes are replaced by pipe sources connected to the loudspeaker.

Modeling groundwater-level responses to multiple stresses using transfer-function models and wavelet analysis in a coastal aquifer system

In coastal aquifers, dynamic stresses such as climate forcings, groundwater withdrawals, and ocean tidal fluctuations cause nonlinear responses to groundwater levels. Such responses to the stresses impact groundwater resources and related flooding and infrastructure risks at multiple scales. We used time-series models such as transfer-function models and wavelet analysis to quantify the relative contribution of these stresses to groundwater-level fluctuation in wells from the unconfined and confined aquifers in an Atlantic coastal aquifer. Climate forcings, such as precipitation and temperature, explained most of the groundwater-level variation for wells in the unconfined aquifer, whereas groundwater withdrawals were the dominant driver of groundwater levels for wells in the confined aquifer. The impact of groundwater withdrawals also was detected in several wells in the unconfined aquifer. Although the influence of ocean tides on groundwater levels commonly is observed in coastal aquifers, we found that daily groundwater withdrawals can obscure the semi-diurnal coherence signal of the two series. The magnitude of groundwater-level fluctuation that could be explained solely by tides was minor compared to that explained by climate or withdrawal stresses. Transfer-function modeling showed seasonal withdrawals from wells in confined aquifers had a significant, yet heterogeneous influence on groundwater levels in coastal aquifers, which highlights climate and withdrawals as key compounding stresses in coastal hydrology. This study demonstrates the value of time-series approaches to advance characterization of groundwater systems in areas with limited hydrogeologic parameter information.

Research on the Current Control Strategy of a Brushless DC Motor Utilizing Infinite Mixed Sensitivity Norm

During the brushless DC (BLDC) motor working process, the system encounters inevitable uncertainties. These ambiguities stem from potential fluctuations, random occurrences, measurement inaccuracies, varying operational conditions, environmental shifts such as temperature alterations, among other factors. Uncertainties, an inherent aspect of any real control system, can be broadly classified into two categories: sensor signal uncertainties and discrepancies between the mathematical and actual models due to parameter perturbations. To mitigate the impact of sensor noise and parameter perturbations on the BLDC motor, a robust control strategy utilizing infinite norm mixed sensitivity based on PI control strategy (PI-H∞-MIX) is proposed in this paper. Firstly, the closed-loop control structure and transfer function model of the BLDC motor control system current loop are analyzed based on the current loop circuit topology, and then, the model parameters perturbation is analyzed, and the multiplicative uncertainty bound is given. In addition, the appropriate weighting function is selected to ensure the robustness of the system. In this case, the controller design problem is transformed into the H∞ standard control problem, and then, the system augmentation matrix is established, and the controller is solved by Matlab/Simulink. Finally, the performances of the traditional PI control strategy and the PI-H∞-MIX are compared and analyzed. The results show that (1) the proposed PI-H∞-MIX strategy can improve the control system robustness under the parameter perturbation condition effectively, and (2) the proposed PI-H∞-MIX strategy can suppress the noise signal of the sensor.

One-Step Ahead Control Using Online Interpolated Transfer Function for Supplementary Control of Air-Fuel Ratio in Thermal Power Plants

Recently, the environmental problem has become a global issue. The air to fuel ratio (AFR) in the combustion of thermal power plants directly influences pollutants and thermal efficiency. A research result was published showing that the AFR control performance of thermal power plants can be improved through supplementary control using dynamic matrix control (DMC). However, online optimization of DMC needs an extra computer server in implementation. This paper proposes a practical AFR control with one-step ahead control which does not use online optimization and can be implemented directly in existing distributed control system (DCS) of thermal power plants. Closed-loop transfer function models at three operating points are independently developed offline. Then, an online transfer function using interpolation of offline models is applied at each sampling step. A simple one-step ahead control with online transfer function is applied as a supplementary control of AFR. Simulations with two different type power plants, a 600 MW oil-fired drum-type power plant and a 1000 MW ultra supercritical (USC) coal-fired once-through type power plant, are performed to show the effectiveness of the proposed control structure. Simulation results show that the proposed supplementary control can effectively improve the conventional AFR control performance of power plants.

Study on dynamic control system of tunnel variable air volume ventilation based on first-order delay and predictive compensation control model

Using a variable air volume ventilation system is an efficient way to save energy in the tunnel. To address the issues of low control parameter accuracy and high operating energy consumption, the transient flow field and ventilation resistance characteristics were analyzed using conservation equations, and the first-order delay mathematical model of tunnel ventilation control was established by taking tunnel and jet fan parameters into account. The airflow dynamic control model's related parameters and transfer function were also solved. The overshoot, steady value, and adjustment time of the control system were evaluated using simulation and experiment. In full-scale experiments, the required wind speed was converted into the frequency of the jet fans to achieve variable air volume ventilation control. The results show that the variable air volume ventilation control system has the characteristics of nonlinear, and the first-order delay time transfer function is related to the 1/2-th power of ventilation resistance and pressure. The control system performs well, and the response parameters are all within the error range. Moreover, the discussion results of the comparative tests also illustrated that the purpose of dynamic wind speed adjustment could be achieved through frequency conversion control.

Position control of Stewart platform with electric linear actuator

In recent decades, several technological applications have depended on manipulators like Stewart platform due to its accuracy and precision. Based on actuation type, Stewart platforms could be rotary or linearly actuated. Electric linear actuators are devices commonly consist of DC or AC motors coupled with lead screw or mechanism of gears and spindle which are used to convert rotary motion into linear (push or pull) motion. To increase accuracy and precision and achieve the desired linear actuator response, controllers should be used. The main aspiration of this work is to investigate the feasibility of using PID controllers for position control of Stewart platform with linear actuators. The mathematical model has been derived and the model transfer function has been obtained. To meet the required response of performance characteristics, the PID controller has been designed based on analysis of root-locus. Model simulation analysis has been carried out on both MATLAB and Simulink. For the electric linear actuator, comparison between the obtained response and the results of Ziegler-Nichols tuning method has been discussed on basis of the specifications of the time response. The PID controller parameters for the electric linear actuator has been tested experimentally and compared with simulation results.

Improvement of predictive control algorithm based on fuzzy fractional order PID

Abstract The existing predictive control strategy has comprehensive prior knowledge of the controlled process, requires weak continuity of the search space for parameter optimization, and its application is limited to some extent. Therefore, improved research on the fuzzy fractional proportional integral differential (PID) predictive control algorithm is proposed. First, the control principle of PID predictive control equipment is proposed. According to this principle, the structure of the PID predictive control equipment adaptive fuzzy PID energy-saving controller is constructed. Through the PID energy-saving control parameter setting principle and fuzzy control rules, the adaptive fuzzy PID energy-saving control of PID predictive control equipment is realized. Finally, the fractional order PID predictive transfer function model is constructed to improve the predictive control algorithm based on PID optimization technology. The experimental results show that the accuracy and efficiency of the designed algorithm can get the best performance index, and its stability, overshoot, time, and control accuracy are basically unchanged. In the small area temperature control, the disturbance interference is small, the anti-disturbance ability is good, and it has strong robustness.

MEMS Differential Pressure Sensor with Dynamic Pressure Canceler for Precision Altitude Estimation.

Atmospheric pressure measurements based on microelectromechanical systems (MEMSs) can extend accessibility to altitude information. A differential pressure sensor using a thin cantilever and an air chamber is a promising sensing element for sub-centimeter resolution. However, its vulnerability to wind and the lack of height estimation algorithms for real-time operation are issues that remain to be solved. We propose a sensor "cap" that cancels the wind effect and noise by utilizing the airflow around a sphere. A set of holes on the spherical cap transmits only the atmospheric pressure to the sensor. In addition, we have developed a height estimation method based on a discrete transfer function model. As a result, both dynamic pressure and noise are suppressed, and height is estimated under a 5 m/s wind, reconstructing the trajectory with an estimation error of 2.8 cm. The developed sensing system enhances height information in outdoor applications such as unmanned aerial vehicles and wave height measurements.

On the flame transfer function models for laminar premixed conical and V- flames considering the stretch effect

This paper investigates a predictive model that considers the impact of stretch on the dynamic response of laminar premixed conical and V- flames; the flame stretch consists of two components: the flame curvature and flow strain. The steady and perturbed flame fronts are determined via the linearized G-equation associated with the flame stretch model. Parameter analyses of the effects of Markstein length L, flame radius R and unstretched flame aspect ratio β are also conducted. Results show that the flame stretch reduces the steady flame height, with this effect being more significant for larger Markstein lengths and smaller flame sizes. The effects of flame stretch on perturbed flames are evaluated by comparing the flame transfer function (FTF) considering the flame stretch and not. For flames of different sizes, the impact of flame stretch on FTF gain can be divided into three regions. When both β and R are relatively small, due to the decrease in steady flame height and the impact of flow strain, the FTF gain increases. As β and R gradually increase, the FTF gain of the conical flame oscillates periodically while the FTF gain of the V-flame decreases, primarily due to the flame curvature enhancing the flame front disturbance and the wrinkle counteracting effect. When β and R are large, a disruption in wrinkle counteracting effect ensues, leading to a significant increase in FTF gain. Furthermore, as the actual flame height is reduced, the flame stretch also reduces the FTF phase lag which is related to the disturbance propagation time from the flame root to the tip.

Modeling of flame transfer function of a diverging premixed flame with developing flame speed under velocity disturbances

Modeling of flame transfer function of a diverging premixed flame with developing flame speed under velocity disturbances

Enhancing acoustic contrast while tracking acoustic transfer functions: A simultaneous control approach

In the context of sound zone control (SZC) systems, the ability to effectively track variations in acoustic transfer functions is essential due to the inevitable variation of acoustic environments. This paper addresses the non-uniqueness problem encountered in time domain SZC, arising from the coupling observed in multichannel transfer function modeling. To address this issue, the utilization of time-varying control filters is proposed, which offers a viable solution. In order to ensure a stable acoustic contrast performance regardless of environmental changes, as well as to mitigate extreme distortion resulting from maximal acoustic contrast (AC) in the time domain, the paper focuses on the objective of maintaining a desired level of AC while tracking the acoustic transfer functions. Simulations are carried out to evaluate the proposed method, demonstrating its capability to effectively track environmental changes and continually update the control filters, consequently providing a stable acoustic contrast performance.

TRANSFER FUNCTION AND ARIMA MODEL FOR FORECASTING BI RATE IN INDONESIA

Fluctuating gold prices can have an impact on various sectors of the economy. Some of the impacts of rising and falling gold prices are inflation, currency exchange rates, and the value of the Bank Indonesia benchmark interest rate (BI Rate). The data was taken from the Indonesian Central Statistics Agency's official website (BPS) for the Bank Indonesia benchmark interest rate (BI Rate) value. Therefore, research on the value of the Bank Indonesia benchmark interest rate (BI Rate) is essential with the gold price as a control. The purpose of this study is to forecast the value of the Bank Indonesia reference interest rate (BI Rate) with a transfer function model where the input variable used is the price of gold and forecast the value of the Bank Indonesia benchmark interest rate (BI Rate) with the ARIMA model. The analysis results show that the best model for forecasting the Bank Indonesia reference interest rate (BI Rate) is a transfer function model with a value of , , , and a noise series model with the MAPE value is