Calculation Of Weighting Factors Research Articles

Unidirectional Finite Control Set-Predictive Torque Control of IPMSM Fed by Three-Level NPC Inverter with Simplified Voltage-Vector Lookup Table

This paper proposes a unidirectional finite control set-predictive toque control (UFCS-PTC) method for a three-level neutral-point-clamped (3L-NPC) inverter fed interior permanent magnet synchronous motor (IPMSM). The proposed algorithm can lower the complexity of PTC fed by 3L-NPC by reducing the number of admissible voltage vectors (VVs) effectively. The candidate VVs are restricted within 60° of the voltage space voltage diagram (VSVD), which is the nearest to the flux trajectory for each 60° flux sector. After the segmentation of the VSVD and flux trajectory, the proposed method can keep VVs in one direction during the prediction process, which can result in significant torque/flux reduction. Therefore, the UFCS-PTC can reduce the number of admissible VVs from twenty-seven to six while achieving excellent steady-state performance in terms of reduced flux and torque ripples. Additionally, the proposed method eliminates the need for weighting factor calculation for neutral point voltage associated with a 3L-NPC inverter. The UFCS-PTC of IPMSM also has other features, such as improved balancing capability of the DC-link capacitors’ voltage, small computation time due to the reduced number of admissible voltage vectors considered in the cost function, and easy implementation. The effectiveness of the proposed method is verified through experimental results.

Latest Advances of Model Predictive Control in Electrical Drives—Part I: Basic Concepts and Advanced Strategies

The application of model predictive control in electrical drives has been studied extensively in the past decade. This article presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this article aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.

Low Complexity Model Predictive Flux Control for Three-Level Neutral-Point Clamped Inverter-Fed Induction Motor Drives Without Weighting Factor

Tuning of weighting factors is a very complex task in the implementation of conventional finite set predictive torque control (FS-PTC) for three-level neutral-point-clamped (3L-NPC) inverter fed IM drive. The choice of these weighting factors strongly influences the control objectives such as flux, torque, and neutral point voltage (NPV). Moreover, the computational burden is high as all 27 switching states are enumerated for the evaluation of a cost function involving multiple objectives. To reduce the complexity of the conventional FS-PTC, this article proposes a high-efficient single-vector-based predictive flux control for an IM drive fed by a 3L-NPC inverter. The proposed cascaded predictive flux and NPV control evaluates 13 vectors for outer predictive flux control and two switching states for the inner predictive NPV control. It significantly reduces the computational load as the number of enumerations is reduced by more than 50%. The nontrivial process of weighting factor calculation is no longer required. The complexity reduction and the elimination of weighting factors are achieved without sacrificing the transient and steady-state performances in terms of torque and stator flux responses, total harmonic distortion of stator currents, NPV variation, and average switching frequency, compared to the conventional method as verified by experimental results.

Efficient Hybrid Method of FEA-Based RSM and PSO Algorithm for Multi-Objective Optimization Design for a Compliant Rotary Joint for Upper Limb Assistive Device

This paper proposes an efficient hybrid methodology for multi-objective optimization design of a compliant rotary joint (CRJ). A combination of the Taguchi method (TM), finite element analysis (FEA), the response surface method (RSM), and particle swarm optimization (PSO) algorithm is developed to solving the optimization problem. Firstly, the TM is applied to determine the number of numerical experiments. And then, 3D models of the CRJ is built for FEA simulation, and mathematical models are formed using the RSM. Subsequently, the suitability of the regression equation is assessed. At the same time, the calculation of weight factors is identified based on the series of statistical equations. Based on the well-established equations, a minimum mass and a maximum rotational angle are simultaneously optimized through the PSO algorithm. Analysis of variance is used to analyze the contribution of design variables. The behavior of the proposed method is compared to the adaptive elitist differential evolution and cuckoo search algorithm through the Wilcoxon signed rank test and Friedman test. The results determined the weight factors of the mass and rotational angle are about 0.4983 and 0.5017, respectively. The results found that the optimum the mass and rotational angle are 0.0368 grams and 59.1928 degrees, respectively. It revealed that the maximum stress of 335 MPa can guarantee a long working time. The results showed that the proposed hybrid method outperforms compared to other evolutionary algorithms. The predicted results are close to the validation results. The proposed method is useful for related engineering fields.

Big 5 ASEAN capital markets forecasting using WEMA method

ASEAN through ASEAN Economics Community (AEC) 2020 treaty has proposed financial integration via capital markets integration in order to aim comprehensive ASEAN economic integration. Therefore, the need to have a proper prediction of ASEAN capital market becomes a major issue. In this study, we took big 5 ASEAN capital markets, i.e. Straits Times Index (STI), Kuala Lumpur Stock Exchange (KLSE), Stock Exchange of Thailand (SET), Jakarta Stock Exchange (JKSE), and Philippine Stock Exchange (PSE) to be forecasted using WEMA method. Weighted Exponential Moving Average (WEMA) is a new hybrid moving average method which combines the weighting factor calculation in Weighted Moving Average (WMA) with the procedure of Exponential Moving Average (EMA). WEMA has successfully been implemented and used to forecaste discrete time series data, but never being used to forecast ASEAN capital markets. In this study, we took further action by implementing the WEMA method with brute force approach for scaling factor tuning on big 5 ASEAN capital markets. From the experimental results, we found that WEMA has successfully forecasted all those exchanges. By looking at the forecast error measurement, it gives the best performance on PSE and worst performance on SET dataset among all datasets being considered in this study.

Prediction of nontidal sea level variations in the Persian Gulf using data assimilation techniques

ABSTRACTThe regular pattern of tidal water level fluctuation in the open seas is often deviated by the effect of weather systems. The stochastic behavior of these systems makes it difficult to predict the nontidal residuals (NTR) precisely. The hydrodynamic models as efficient tools for the simulation of NTR may suffer from lack of accuracy due to approximate boundary conditions and forcings. Data Assimilation (DA) techniques combine hydrodynamic model predictions with available field observations to improve the predictions. In this study, a number of DA methods were employed to improve the NTR predictions in a semienclosed basin. The results have shown the studied DA techniques, which are originally developed for weather prediction problems, can be improved by considering the physical mechanisms of NTR generation. A new formula was introduced for the calculation of weight factors of the existing methods. Application of the proposed method increased the accuracy of NTR predictions significantly so that the correlation coefficient of the NTR predictions increased from 0.660 to 0.896 and the root mean square error decreased from 5.22 cm to 2.51 cm. In addition, so it is concluded among the studied DA schemes, Barnes method has better efficiency for prediction of NTR in the region.

Weighting Factor Selection Techniques for Predictive Torque Control of Induction Motor Drives: A Comparison Study

For the last few years, predictive torque control (PTC) has attracted the attention of the researchers due to its simplicity and effectiveness. In PTC, flux-weighting factor needs to be wisely adjusted since it affects greatly the performance of the drive system. Many research trials were devoted to select this weighting factor or even eliminate it. Each of these trials illustrates a method to overcome this problem and presents a solution to the conventional weighting factor calculation method. This paper presents a critical evaluation of the performance of recently proposed methods for weighting factor selection for finite control set PTC. Based on the way the weighting factor is calculated, the methods are classified to offline and online methods. In this study, more focus will be directed to the evaluation of the online methods since they can update the weighting factor automatically if the operating point changes. Specifically, four recently developed methods along with the conventional method are considered in this study. Flux ripple, torque ripple, current total harmonic distortion, and average switching frequency are adopted as the judging criteria for this comparison. Simulations at different operating points are used to assess the performance of each method, and the characteristics of each method are compared according to the performance indices suggested. The strengths and weaknesses of each method are highlighted. Therefore, the suitable method can be identified according to different application requirements.

Brown’s Weighted Exponential Moving Average Implementation in Forex Forecasting

In 2016, a time series forecasting technique which combined the weighting factor calculation formula found in weighted moving average with Brown’s double exponential smoothing procedures had been introduced. The technique is known as Brown’s weighted exponential moving average (B-WEMA), as a new variant of double exponential smoothing method which does the exponential filter processes twice. In this research, we will try to implement the new method to forecast some foreign exchange, or known as forex data, including EUR/USD, AUD/USD, GBP/USD, USD/JPY, and EUR/JPY data. The time series data forecasting results using B-WEMA then be compared with other conventional and hybrid moving average methods, such as weighted moving average (WMA), exponential moving average (EMA), and Brown’s double exponential smoothing (B-DES). The comparison results show that B-WEMA has a better accuracy level than other forecasting methods used in this research.

Distributed State Estimation of Smart Grids with Packet Losses

AbstractThis paper explores the problem of distributed state estimation including packet losses for the environment‐friendly renewable microgrid incorporating electricity generating circuits. The problem is becoming critical due to the global warming, increasing green house gas emissions, and practical infeasibility with computational burden of the large‐scale centralized power system monitoring. To address the impending problem, a novel distributed state estimation algorithm is derived in the context of smart grids. Specifically, after modelling the microgrid, this paper proposes a local state estimation algorithm considering packet losses. Then a novel optimal weighting factor calculation method for the global state estimation is proposed. Particularly, it can automatically adjust the optimal weighting factors for different sensor measurements based on the observation. Simulations results show that the desired state estimation accuracy is achieved.

Predictive torque and flux control of an induction machine drive using fuzzy multi-criteria decision making

Among the numerous direct torque control techniques, the finite-state predictive torque control (FS-PTC) has emerged as a powerful alternative as it offers the fast dynamic response and the flexibility to optimize multiple objectives simultaneously. However, the implementation of FS-PTC for multiple objectives optimization requires the optimization of a single objective function, which is constructed using weighting factors as a linear combination of individual objective functions. Traditionally, the weighting factors are determined through a non-trivial process, which is a complex and time-consuming task. In an effort to avoid the time-consuming task of weighting factor selection, this paper aims at replacing the weighting factor calculation with a systematic fuzzy multiple-criteria decision making in which the individual objective functions may have equal or varying degrees of importance. As a result the weighting factor calculation can be completely avoided. The simulation and experimental tests are conducted on a 2.2 kW induction motor drive to validate the proposed approach. The result outcomes are compared with the conventional predictive torque control (PTC) using weighting factors on the same experimental platform.

The calculation of weight factors for performance evaluation of soccer through Analytic Hierarchy Process

The calculation of weight factors for performance evaluation of soccer through Analytic Hierarchy Process

Computation of ex-core detector weighting functions for VVER-440 using MCNP5

The paper deals with the problem of weighting factor calculation and the determination of spatial weighting functions of ex-core detectors for VVER-440 using the Monte Carlo method. The computational results were obtained by the well-known code MCNP5 allowing high performance three-dimensional modeling of complex geometry of the in-vessel and ex-vessel reactor parts. Despite the fact that adjoint methods dominate in practice, forward mode of code running was chosen and applied to provide more accurate results contrary to the adjoint one. The calculation was performed for a boron lined proportional counter CPNB44 installed at the 3rd unit of NPP Jaslovské Bohunice. The base is the calculation of ex-core detector reaction rate induced by a neutron generated in a given volume element of a fuel pin. All the geometrical details and arising space heterogeneities were taken into account with the highest accuracy in the complex reactor model. Having obtained computational results, the weighted least square method was used to fit axial weighting functions. With respect to horizontal direction, the polyhedral approximation of closed Jordan surfaces was used to find the proper shape of horizontal weighting factor distribution. Sensitivity and parametric analysis was performed to evaluate the influence of various reactor operational parameters as well as the ex-core detector positioning on the weighting function values.

Investigation and Evaluation of Water Quality of the East Lake, Wuhan

The East Lake of Wuhan, as a famous scenic area, has been seriously polluted with the influences of human activity. This paper sets up 7 monitoring points (D1～D7) along the East Lake according to the characteristics of point and non-point source pollution, to investigate and evaluate the current situation of water quality on the basis of fuzzy evaluation method. In which, the evaluation factors used for calculation of weight factors are different for lake water collected from different monitoring points. Results showed that the water quality of D3 is at Grade I and that of the other 6 monitoring points are all worse than Grade V. It was deduced that the D3 water was purified by aquatic plant of water lilies, while D1, D2, D4～D7 water were seriously polluted by the wastewater from household, hotels and restaurants, which was without any treatments and discharged into the East Lake directly. In addition, the pollutants from running vehicles on the bank of East Lake possibly went into this lake in the rain or snow weather and brought the lake water pollution. Therefore, some measures of controlling the direct discharge of wastewater from pollution sources, planting aquatic plants in the lake area and separating the lake from roads by a parkway, should be taken to protect the East Lake water environment and improve its water quality.

Simulated Tempering Distributed Replica Sampling, Virtual Replica Exchange, and Other Generalized-Ensemble Methods for Conformational Sampling.

Generalized-ensemble algorithms in temperature space have become popular tools to enhance conformational sampling in biomolecular simulations. A random walk in temperature leads to a corresponding random walk in potential energy, which can be used to cross over energetic barriers and overcome the problem of quasi-nonergodicity. In this paper, we introduce two novel methods: simulated tempering distributed replica sampling (STDR) and virtual replica exchange (VREX). These methods are designed to address the practical issues inherent in the replica exchange (RE), simulated tempering (ST), and serial replica exchange (SREM) algorithms. RE requires a large, dedicated, and homogeneous cluster of CPUs to function efficiently when applied to complex systems. ST and SREM both have the drawback of requiring extensive initial simulations, possibly adaptive, for the calculation of weight factors or potential energy distribution functions. STDR and VREX alleviate the need for lengthy initial simulations, and for synchronization and extensive communication between replicas. Both methods are therefore suitable for distributed or heterogeneous computing platforms. We perform an objective comparison of all five algorithms in terms of both implementation issues and sampling efficiency. We use disordered peptides in explicit water as test systems, for a total simulation time of over 42 μs. Efficiency is defined in terms of both structural convergence and temperature diffusion, and we show that these definitions of efficiency are in fact correlated. Importantly, we find that ST-based methods exhibit faster temperature diffusion and correspondingly faster convergence of structural properties compared to RE-based methods. Within the RE-based methods, VREX is superior to both SREM and RE. On the basis of our observations, we conclude that ST is ideal for simple systems, while STDR is well-suited for complex systems.

The calculation of weight factors for tristimulus integration

AbstractThis article defines the method of calculation of weight sets for tristimulus integration published by the ASTM in its Method E 308–85. The preparation of weight sets for any measurement interval or wavelength range by Lagrange cubic interpolation from standard tables of data at other intervals is described. In addition, methods of truncating weight sets to wavelength ranges of less than 360 nm to 830 nm are discussed. The importance of calculating and maintaining the chromaticity of the neutral point is noted. An example of calculation of a set of weights is given in an Appendix, along with an example computer program that will calculate a set of weights at 20 nm intervals from standard illuminant‐observer data given at 1 nm intervals.