Variable impedance control has been required to perform a variety of interactive tasks in contact with environments. In some cases, the time-varying stiffness matrix of the impedance model can be used to achieve high performance for uneven contact ta...
A zero-ripple input current is known to improve the lifetime of battery sets and fuel cells and to assure maximum power point tracking in PV panels. To perform current ripple elimination in a floating interleaved boost converter (FIBC), one of the ty...
Groundwater level prediction is essential for sustainable water resource management. Although machine learning models are widely applied, input variable selection critically affects predictive performance, and existing studies rarely evaluate model p...
This research proposes a methodology for the selection of input variables based on eXplainable AI (XAI) for energy consumption prediction. For this purpose, the energy consumption prediction model (R2 = 0.871; MAE = 2.176; MSE = 9.870) was selected b...
In order to reduce the online calculations for power system simulations of transient stability, and dramatically improve numerical integration efficiency, a transient stability numerical integration algorithm for variable step sizes based on virtual...
In Korea apartment buildings, most energy is consumed as heating energy. In order to reduce heating energy in apartment buildings, it is required to reduce the amount of energy used in heating systems. Energy saving in heating systems can be achieved...
A large input delay, parametric uncertainties, matched disturbances and mismatched disturbances exist extensively in variable air volume air-conditioning systems, which can deteriorate the control performance of the room temperature and even destabil...
The four-switch Buck-Boost (FSBB) converter can produce voltage conversion within a wide input voltage range, which is suitable for variable-speed permanent magnet synchronous generator (PMSG) energy storage systems with AC inputs and DC outputs. To...
River water temperature connects hydrodynamic processes, air–water heat exchange, and aquatic ecological responses. Although data-driven models are increasingly used for short-term water-temperature forecasting, input-variable choice still infl...
For control applications, the angular velocity of the drive crank of a four-bar mechanism is traditionally assumed to be constant. In this paper, we propose control of variable velocity of the drive crank to obtain the desired output motions for the...
Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure...
Introduction: Human joint moment is a critical parameter to rehabilitation assessment and human-robot interaction, which can be predicted using an artificial neural network (ANN) model. However, challenge remains as lack of an effective approach to d...
After decades of economic development in China, its energy consumption still relies heavily on coal, and the dominant segment of our economy—the industrial sectors with large coal input—have caused massive wastewater pollution. To provide...
This paper presents a new procedure for designing a fractional order unknown input observer (FOUIO) for nonlinear systems represented by a fractional-order Takagi–Sugeno (FOTS) model with unmeasurable premise variables (UPV). Most of the curren...
Recently, an increase in wildfire incidents has caused significant damage from economical, humanitarian, and environmental perspectives. Wildfires have increased in severity, frequency, and duration because of climate change and rising global tempera...
We examined the consequences of within-category phonetic variability in the input on non-native learners’ production accuracy. Following previous empirical research on the L2 acquisition of phonetics and the lexicon, we tested the hypothesis th...
The importance and urgency of improving energy and carbon emissions efficiency in mitigating climate change and achieving carbon neutrality have become an increasingly relentless focus in recent years. Assessing the performance of energy saving and c...
Reduced body movement and weakened musculoskeletal function as a result of aging increase the risk of falls and serious physical injuries requiring medical attention. To solve this problem, a fall prevention algorithm using an acceleration sensor has...
In this paper, we consider the transient state behavior of a segmented thermoelectric generator (STEG) exposed to a variable heat input power on the hot side while the transfer of heat on the cold side is by natural convection. Numerical analysis is...
The profession debates how to encode a categorical variable for input to machine learning algorithms, such as neural networks. A conventional approach is to convert a categorical variable into a collection of binary variables, which causes a burdenso...
In Long Short-Term Memory (LSTM)-based runoff forecasting models, the selection of input schemes is critically important. This study, using daily rainfall and runoff data from the Jingle Basin (2006–2014), investigated three input schemes to ev...
This study addresses the problem of simultaneous variable selection and model estimation in multivariate failure time data, a common challenge in clinical trials with multiple correlated time-to-event endpoints. We propose a unified framework that id...
The Cuk power factor correction (PFC) converter with an input inductor operating discontinuous conduction mode (DCM) is widely utilized for its advantages of continuous input and output currents, low output voltage ripple, and simple control. However...
The controller design of vehicle systems depends on accurate reference index input. Considering information fusion and feature extraction based on existing data settings in the time domain, if reasonable input is selected for prediction to obtain acc...
In this paper, a single-phase photovoltaic (PV) inverter fed by a boost converter to supply a freezer motor with variable DC input is investigated. The proposed circuit has two stages. Firstly, the DC output of the PV panel that varies between 150 an...
Feed is the largest variable cost for dairy farms in Australia, and dairy farmers are faced with the challenge of profitably feeding their cows in situations where there is significant variation in input costs and milk price. In theory, the addition...
For boost power factor correction (PFC) converters operating in critical conduction mode (CRM), charge compensation strategies are utilized to improve input current distortion. However, since massive calculations are required under complex working co...
Design of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concer...
Robotic Friction Stir Welding (RFSW) technology integrates the advantages of friction stir welding and industrial robots, finding extensive applications and research in aerospace, shipbuilding, and new energy vehicles. However, the high-speed rotatio...
This paper presents a new method for the simultaneous estimation of system states and unknown inputs in fractional-order Takagi–Sugeno (FO-TS) systems with unmeasurable premise variables (UPVs), by introducing a fractional-order proportional-in...
Various regression models are currently applied to derive functional forms of operating rules for hydropower reservoirs. It is necessary to analyze and evaluate the model selecting uncertainty involved in reservoir operating rules for efficient hydro...
Accurate generation prediction at multiple time-steps is of paramount importance for reliable and economical operation of wind farms. This study proposed a novel algorithmic solution using various forms of machine learning techniques in a hybrid mann...
We propose a method, called bi-point input, for convolutional neural networks (CNNs) that handle variable-length input features (e.g., speech utterances). Feeding input features into a CNN in a mini-batch unit requires that all features in each mini-...
LIDARs produce depth measurements, which are relatively sparse when compared with cameras. Current state-of-the-art solutions for increasing the density of LIDAR-derived depth maps rely on training the models for specific input measurement density. T...
With the increase in on-orbit maintenance and support requirements, the application of space manipulator is becoming more promising. However, how to control the vibration generated by the space manipulator has been a difficult problem to be solved. T...
This study develops a late spring-early summer rainfall forecasting model using an artificial neural network (ANN) for the Geum River Basin in South Korea. After identifying the lagged correlation between climate indices and the rainfall amount in Ma...
This work investigates non-fragile guaranteed cost control (NFGCC) of a class of fractional delay systems of variable-order subject to parametric uncertainty and varying control input delay. Adopting fractional-order (FO) Lyapunov theory along with t...
Utilizing spatial diversity, the distributed multiple-input multiple-output (MIMO) radar has the potential advantage of improving system detection performance. In this paper, the incoherent detection performance of distributed multiple-input multiple...
Near-infrared spectroscopy supports rapid quantification of moisture, oil, protein, and starch in corn. Their prediction models may require different spectral inputs, complicating shared-variable selection. We developed the multicomponent shared wave...
In this paper, a variable gain prescribed performance control law is proposed for dynamic positioning (DP) of ships with positioning error constraints, input saturation and unknown external disturbances. The error performance index functions are desi...
The main goal of this study was to derive small-signal models of the input characteristics of buck, boost, and flyback converters working in continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The models presented in the paper w...
Variability in the response of individuals to various non-invasive brain stimulation protocols is a major problem that limits their potential for clinical applications. Baseline motor-evoked potential (MEP) amplitude is the key predictor of an indivi...
This paper proposes new ANOVA-based approximations of functions and emulators of high-dimensional models using either available derivatives or local stochastic evaluations of such models. Our approach makes use of sensitivity indices to design adequa...
A DC converter with the benefits of reverse power capability, less switching loss and wide voltage operation is presented and implemented for wide input voltage applications such as fuel cell energy, photovoltaic (PV) system and DC wind power. Two fu...
This paper introduces a novel power supply voltage adjustment strategy that can determine the optimum voltage value based on the amount of absorbed power. The novel automatic voltage adjustment technique was called inverse maximum power point trackin...
Agricultural production is increasingly threatened by climate variability, limited access to quality inputs, and market shocks in developing countries. Insurance–input bundles, which integrate crop insurance with inputs like fertiliser and seed...
Adaptive filtering algorithms often suffer from biased parameter estimation and performance degradation in the presence of colored input noise and impulsive observation noise, both of which are common in practical sensor and communication systems. Ex...
Morphing aircraft can alter their aerodynamic configuration to obtain multitask adaptability and improve flight performance. In this paper, we apply the variable sweep concept on a tandem-wing micro aerial vehicle (MAV) for multitask adaptability, th...
Machine-learning-based models are used to predict dissolved oxygen (DO); however, acquiring continuous water quality data for input variables in harsh environments remains challenging. Herein, redox potential (ORP) determined by a thermo-treated flex...
Recent studies have shown benefits of using tidal stream and wave energy in the electricity generation mix to improve supply–demand balancing on annual/subannual timeframes. This paper investigates this further by considering the variability of...
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