Scalar Algorithm Research Articles

Current balancing of scalar-controlled induction motors with long imbalanced cables for artificial lift systems

Induction motor current imbalance increases losses, torque ripple and vibrations. Current imbalance is known to appear in artificial lift systems, where motors are driven over long imbalanced cables. Power hardware modifications, namely transposition of cable phases in the wellbore, adjustment of the step-up transformer taps, and addition of balancing inductors have so far been proposed to suppress the imbalance. However, these solutions compromise the system's reliability or involve costly additional equipment, which must be customized according to the cable characteristics. This paper proposes a control method for current balancing of induction motors driven by scalar-controlled variable speed drives. In the proposed method, Second-Order Generalized Integrators (SOGIs) are used to extract the negative-sequence component of the motor currents, which is then suppressed by a Synchronous Reference Frame (SRF) current controller. The frequency and angle information required by the SOGIs and the SRF controller are obtained directly from the scalar algorithm, without needing a position sensor or observer, thus offering a novel, simple, robust and computationally effective implementation, which is also independent of the cable characteristics. The paper presents MATLAB/Simulink simulation results to illustrate the method's operating principles and performance in a variety of transient conditions. Experimental results obtained using full-scale equipment are also provided to demonstrate its effectiveness.

INTERPOLATION OF TABULAR FUNCTIONS FROM ONE INDEPENDENT VARIABLE USING THE TAYLOR POLYNOMIAL

A method of local interpolation of tabular functions from one independent variable using the Taylor polynomial of the nth degree in arbitrarily located interpolation nodes has been developed. This makes it possible to calculate intermediate values of tabular functions between interpolation nodes. The conducted analysis of the latest research and publications in the field of interpolation of tabular functions showed that the main part of the research is a strict theory of interpolation, i.e. clarification of its fundamental mathematical provisions. Some features of the interpolation of tabular functions from one independent variable using the Taylor polynomial of the nth degree are considered, namely: the solution algorithm and mathematical formulation of the interpolation problem are given; its formalized notation is given, as well as the matrix notation of interpolation procedures for certain values of the argument. A scalar algorithm for solving the problem of interpolation of tabular functions from one independent variable using the Taylor polynomial of the 2nd, 3rd, and 4th degrees has been developed. The simplicity and clarity of this algorithm is one of its advantages, but the algorithm is inconvenient for software implementation. The mathematical formulation of the problem of interpolation of tabular functions in terms of matrix algebra is given. The interpolation task is reduced to performing the following actions: based on the values of nodal points known from the table, it is necessary to calculate the Taylor matrix of the nth degree; based on the function values specified in the table a column vector of interpolation nodes should be formed; solve a linear system of algebraic equations, the root of which is the numerical coefficients of the Taylor polynomial of the nth degree. A method of calculating the coefficients of the interpolant, given by the Taylor polynomial of the nth degree for one independent variable has been developed. The essence of the method reduces to the product of the matrix, inverse of the Taylor matrix, which is determined by the nodal points of the tabular function, by a column vector containing the values of the interpolation nodes. Specific examples demonstrate the peculiarities of calculating the interpolant coefficients of the 2nd, 3rd and 4th degrees for one independent variable, and for each of them the interpolated value of the function at a given point is calculated. Calculations were performed in the Excel environment, which by analogy can be successfully implemented in any other computing environment.

Computing Enclosures for the Matrix Mittag–Leffler Function

We propose two algorithms for numerically calculating interval matrices including two-parameter matrix Mittag–Leffler (ML) functions. We first present an algorithm for computing enclosures for scalar ML functions. Then, the two proposed algorithms are developed by exploiting the scalar algorithm and verified block diagonalization. The first algorithm relies on a numerical spectral decomposition. The cost of this algorithm is only cubic plus that of the scalar algorithm if the second parameter is not too small. The second algorithm is based on a numerical Jordan decomposition, and can also be applied to defective matrices. The cost of this algorithm is quartic plus that of the scalar algorithm. A numerical experiment illustrates an application to a fractional differential equation.

The application of attitude change information in magnetic interference component suppression

Abstract Magnetic interference is one key factor reducing the vector measurement accuracy of geomagnetic field measurement instrument, where scalar suppression algorithm is ineffective. A convenient component suppression method is proposed to avoid complex equipments and strict operations in previous component methods. The key factor is to overcome the problem that additive unknown parameters are added when attitude changes. System attitude change information is proposed for component suppression, where the attitude change is provided by inertial navigation system (INS). After suppression, magnetic interference of north, vertical and east direction are suppressed to 2.1%, 4.28% and 2.53% respectively. It provides a new and convenient way to improve the accuracy of geomagnetic field vector measurement.

Researching of the low-precision SINS research for an unmanned vehicle

A small-sized inertial navigation system (SINS) Gyrolab GL VG 109 is researched. It is shown that this system has low accuracy; therefore it cannot be used to determine the parameters of an unmanned vehicle in an autonomous mode. Correction of the system from the satellite navigation system significantly increases the accuracy of determining the parameters of an unmanned vehicle, but only under conditions of stable signals from the satellite navigation system (SNS). The algorithmic support for the correction facility of the navigation system based on the scalar adaptive estimation algorithm and identification procedure is formed. The use of algorithmic correction of SINS from SNS using an estimation algorithm allows achieving an accuracy that corresponds to systems of the third accuracy class. Keywords inertial navigation system without platform; unmanned vehicle; correction; satellite navigation system; scalar estimation algorithm; scalar identification; analysis of accuracy

Original Approach Toward Three-Phase Indirect Matrix Converters Through Hybrid PWM Modulation and DSP Implementation

Power electronic matrix converters are converters carrying out just one solitary transitional stage. AC-AC conversion automatism in matrix converters is attained through the exploitation of bidirectional controllable power switches associated with a structural matrix. The indirect matrix converter is an alternating preference to the direct matrix converter embodied by AC-DC converter and DC-AC inverter. In this paper, an assemblage of Pulse Width Modulation categories is used to control the dual stages of IMC. AC-DC converter is modulated through the well-known space vector algorithm, while DC-AC inverter is modulated through a novel algorithmic conception referred to as the digital scalar algorithm. Comparative analysis between the conventional DSVPWM modulation and the novel proposed modulation technique is escorted demonstrating that the latter is facilely comprehended and simply put into real-time practice. This paper comes forward with digital signal processor real-time enforcement, conceived for indirect matrix converter. Uniting both original approaches into one topological system entrained a significant decrease of 38% in real-time computation assesses. Throughout the paper, it is well proven that the proposed solution results in high-quality input/output waveforms, and averts from servicing supplementary devices that trigger silicon devices' gates. Numerous experimental enquires within the delivered research reveal advantageous aspects of the contemporary approach from overall simplicity to entire effectiveness.

Simple Efficient Hybridization of Classic Global Optimization and Genetic Algorithms for Multiobjective Optimization

An efficient method combining classical (gradient-based) methods for global scalar optimization and genetic algorithms for multiobjective optimization (MOO) is proposed for approximating the Pareto frontier and the Edgeworth–Pareto hull (EPH) of the feasible objective set in complicated nonlinear MOO problems involving piecewise constant functions of criteria with numerous local extrema. An optima injection method is proposed in which the global optima of individual criteria are added to the population of a genetic algorithm. It is experimentally shown that the method is significantly superior to the original genetic algorithm in the order of convergence and the approximation accuracy. Experiments concerning EPH approximation are also performed for the problem of constructing control rules for a cascade of reservoirs with criteria reflecting the reliability with which the requirements imposed on the cascade are met.

Анализ эффективности работы асинхронной машины с короткозамкнутым ротором при скалярном частотном управлении

The article presents a procedure for analyzing the performance of a frequency controlled induction machine in the case of using a scalar control algorithm with keeping the power losses in the machine itself to a minimum and maintaining constant overload capacity and magnetic flux. The essence of the proposed procedure consists in combining the calculated values of machine parameters obtained from its mathematical model in the case of using frequency control with the analytical expressions characterizing the power loss components. As a result, it becomes possible to determine not only the total power losses in a frequency controlled induction machine, but also changes in its other operating parameters, the reactive power absorbed from the network being the most important one of them. It has been found that with these parameters, i.e., the total power losses in the machine and the absorbed reactive power duly taken into account, it is most expedient to use a control algorithm maintaining constant overloading capacity and magnetic flux at a constant torque on the machine shaft. With the machine shaft torque being of a windage type as determined from the power losses taken in combination with the absorbed reactive power, the best performance is achieved in using the machine control law maintaining its constant overloading capacity: kus = kn k fs w r.

Connecting on the Lattice Based Reductions for Computing the Generators in the ISD Method

In this paper, the generalized Lagrange-Gauss reduction method to generate the generators in ISD method has been proposed. The comparison results on using the generalized Lagrange-Gauss reduction method and generalized extended Euclidean algorithm have been determined. As well as, the connection between the generalized Lagrange-Gauss Reduction and generalized extended Euclidean Algorithm to compute reduced bases to form the ISD generators in ISD elliptic scalar algorithm is presented.

A Real Coded Vector Population-Based Incremental Learning Algorithm for Multi-Objective Optimizations of Electromagnetic Devices

Even though evolutionary algorithm (EA) has now become the standard and paradigm for solving multi-objective design problems, the complexity of its genetic operation is, however, limiting its popularity in engineering applications. Hitherto, there has been insufficient research that addresses the inadequacy of EAs in extracting the characteristic landscape features of an objective function. However, increasing attentions have now been devoted to EAs based on probabilistic models (EAPMs) in computational intelligence studies. A real coded scalar population-based incremental learning algorithm, an EAPM, is proposed for multi-objective optimizations of electromagnetic devices. Major improvements include the design of a generating mechanism for new intermediate solutions, the selection of elite solutions to update the probability matrix, matrix updating formulations, and refinement mechanism for intervals to precisely generate intermediate solution. Also, a methodology to consider quantitatively both the number of improved objectives and the amount of improvements in a specified objective of multi-objective design problems is introduced in fitness assignments. Numerical results on a high frequency and a low inverse problem are reported to showcase the merits of the proposed algorithm.

Simulation of terrestrial carbon equilibrium state by using a detachable carbon cycle scheme

Determining the equilibrium state of terrestrial carbon is a prerequisite for scientific analysis on the carbon cycle. However, the mechanism through which the carbon cycle reaches the equilibrium state remains unclear. Moreover, the carbon cycle in most of the short–term field experiments rarely reaches the equilibrium state. In this study, a detachable carbon cycle (DCC) model was proposed to simulate the equilibrium state of each carbon pool. The model was established based on a pool–and–flux scheme and contained 14 carbon pools, or carbon flow processes, each process could be detached from the main model and evaluated as an independent component. The environmental scalar algorithms of the Integrated Terrestrial Ecosystem Carbon budget model (InTEC) and Community Atmosphere Biosphere Land Exchange (CABLE) were incorporated in the DCC model. Four situations were compared using the two environmental scalar algorithms and model structure (9 vs. 14 carbon pools). Furthermore, the size and turnover time of each carbon pool were analyzed at the equilibrium state. A sensitivity analysis was then conducted to investigate the responses of carbon density and equilibrium time to 12 key parameters of the model. Results indicated that the combination of the CABLE environmental scalar algorithm and 14 pools exhibited improved performance on carbon storage simulation than that of the other combinations, and the effect of the environmental scalar algorithm was considerably larger than that of the carbon pool number. Sensitivity analysis indicated that the carbon density of grassland and cropland was more vulnerable and sensitive to key parameters of the model than that of the other biomes. This study elucidates influencing factors and underlying control mechanisms in the carbon accumulation, and provides a framework for quantitative analysis of each component of the carbon cycle.

Optimizing {0, 1, 3}-NAF Recoding Algorithm Using Block-Method Technique in Elliptic Curve Cryptosystem

The most expensive and time-consuming operation in Elliptic curve cryptosystem is scalar multiplication operation. Optimization of scalar multiplication will substantially enhance the ECC performance. Scalar multiplication can be improved by using an enhanced scalar recoding algorithm that can decrease the number of operations in the scalar representation process. The objective of this research is to introduce an efficient design and implementation of {0,1,3}-NAF scalar recoding algorithm by applying block method technique. The base algorithm has a complex look up table. With block method application on base algorithm, a complex look up table is undesired. Instead a fix look up table is introduced with less computation required for recoding. The Big-O notation is used to measure the complexity and (µs) used to evaluate the running time of base and proposed algorithm.

Two fast algorithms for projecting a point onto the canonical simplex

Two fast orthogonal projection algorithms of a point onto the canonical simplex are analyzed. These algorithms are called the vector and scalar algorithms, respectively. The ideas underlying these algorithms are well known. Improved descriptions of both algorithms are given, their finite convergence is proved, and exact estimates of the number of arithmetic operations needed for their implementation are derived, and numerical results of the comparison of their computational complexity are presented. It is shown that on some examples the complexity of the scalar algorithm is maximal but the complexity of the vector algorithm is minimal and conversely. The orthogonal projection of a point onto the solid simplex is also considered.

Calculation of photon pulse height distribution using deterministic and Monte Carlo methods

Abstract Radiation transport techniques which are used in radiation detection systems comprise one of two categories namely probabilistic and deterministic. However, probabilistic methods are typically used in pulse height distribution simulation by recreating the behavior of each individual particle, the deterministic approach, which approximates the macroscopic behavior of particles by solution of Boltzmann transport equation, is being developed because of its potential advantages in computational efficiency for complex radiation detection problems. In current work linear transport equation is solved using two methods including collided components of the scalar flux algorithm which is applied by iterating on the scattering source and ANISN deterministic computer code. This approach is presented in one dimension with anisotropic scattering orders up to P8 and angular quadrature orders up to S16. Also, multi-group gamma cross-section library required for this numerical transport simulation is generated in a discrete appropriate form. Finally, photon pulse height distributions are indirectly calculated by deterministic methods that approvingly compare with those from Monte Carlo based codes namely MCNPX and FLUKA.

Fast Plastic Integration Algorithm for Damage Prediction in Forming Process Simulations

The iterative Return Mapping Algorithm (RMA) is widely used for the plastic integration owing to its accuracy and efficiency, but it is CPU time consuming and may cause divergence problems in case of large strain increments. This paper presents a fast plastic integration method called Direct Scalar Algorithm (DSA) for the damage prediction in forming process simulations. A simplified three-dimensional (3D) strain-based damage model is coupled with the plasticity and implemented into the DSA which does not need iterative solution to make the plastic integration very fast and robust even for very large strain increments. The basic idea is to transform the constitutive equations in terms of the unknown stress vectors into a scalar equation in terms of the equivalent stresses which can be determined by using the experimental tensile curve; thus, the plastic multiplier ∆λ can be directly calculated. The DSA is as accurate as RMA but much faster for the plastic integration.

Fully vectorial laser resonator modeling of continuous-wave solid-state lasers including rate equations, thermal lensing and stress-induced birefringence.

The computer-aided design of high quality mono-mode, continuous-wave solid-state lasers requires fast, flexible and accurate simulation algorithms. Therefore in this work a model for the calculation of the transversal dominant mode structure is introduced. It is based on the generalization of the scalar Fox and Li algorithm to a fully-vectorial light representation. To provide a flexible modeling concept of different resonator geometries containing various optical elements, rigorous and approximative solutions of Maxwell's equations are combined in different subdomains of the resonator. This approach allows the simulation of plenty of different passive intracavity components as well as active media. For the numerically efficient simulation of nonlinear gain, thermal lensing and stress-induced birefringence effects in solid-state active crystals a semi-analytical vectorial beam propagation method is discussed in detail. As a numerical example the beam quality and output power of a flash-lamp-pumped Nd:YAG laser are improved. To that end we compensate the influence of stress-induced birefringence and thermal lensing by an aspherical mirror and a 90° quartz polarization rotator.

Scalar Method of Fault Diagnosis of Inertial Measurement Unit

The scalar method of fault diagnosis systems of the inertial measurement unit (IMU) is described. All inertial navigation systems consist of such IMU. The scalar calibration method is a base of the scalar method for quality monitoring and diagnostics. In accordance with scalar calibration method algorithms of fault diagnosis systems are developed. As a result of quality monitoring algorithm verification is implemented in the working capacity monitoring of IMU. A failure element determination is based on diagnostics algorithm verification and after that the reason for such failure is cleared. The process of verifications consists of comparison of the calculated estimations of biases, scale factor errors, and misalignments angles of sensors to their data sheet certificate, kept in internal memory of computer. As a result of such comparison the conclusion for working capacity of each IMU sensor can be made and also the failure sensor can be determined.

Accuracy of manual and automated rectal contours using helical tomotherapy image guidance scans during prostate radiotherapy.

94 Background: Prostate radiotherapy can be delivered using daily image-guided helical tomotherapy. Previous work has shown that contouring the rectum on the kV planning CT scan has a Jaccard conformity index (JCI) of 0.78 for different oncologists (inter-observer variability) and 0.82 for a single oncologist (intra-observer variability) (Lutgendorf-Caucig C et al. Feasibility of CBCT-based target and normal structure delineation in prostate cancer radiotherapy: multi-observer and image multi-modality study. Radiother Oncol. 2011;98(2):154-61.). Using the daily image guidance MV CT scan we have developed automated methods to contour the rectum in order to investigate the dose delivered over a course of treatment. We sought to quantify the accuracy of MV manual and automated contours. Methods: A single oncologist (JES) contoured the rectum on 370 MV scans for 10 participants treated with helical tomotherapy to prostate and pelvic lymph nodes. Accuracy of MV manual contours was tested using a scalar algorithm to enlarge and reduce the contours and intra-observer re-contouring at a 3-month interval. Automated contouring, incorporating the Chan-Vese algorithm, was developed and outputs were compared with manual contours. Results: JES could identify differences in MV manual contour size at the level of ±2.2 mm, equivalent to 1.7 pixels. The median JCI for MV re-contouring was 0.87 with inter-quartile range (IQR) 0.78 to 0.90. When compared with manual contours, automated outputs had a median JCI of 0.79 (IQR 0.74 to 0.79). These results were obtained after 3 iterations, each taking less than 10 seconds. Conclusions: Manual contouring using MV scans was accurate, at a level of approximately 2 mm, and reproducible, with JCI of 0.87. The time taken to contour was approximately 20 minutes per scan. Automated contouring was also reproducible with JCI of 0.79 and, in contrast, took less than a minute per scan. Both manual and automated methods produced results comparable to those for contouring using kV scans. We plan to use auto-contouring to calculate accumulated dose to the rectum in an initial cohort of 100 participants. These doses will be correlated with toxicity as part of the VoxTox Study.

Teacher - Student Graphical User Interface For Testing And Comparing The Performance Of Adaptive Algorithms Used In Smart Antenna Networks

AbstractSmart antenna networks are receiving a lot of interest in these days, as new advanced and fast processors are being developed. Capable of pointing the main beam in a certain desired direction and create nulls in the radiation pattern in the direction of interference, smart antenna networks are a good solution in a bandwidth limited environment as the number of users continuously grow. This technique is called beamforming. For many years smart antennas were not practical as they involve the use of a processor that runs an adaptive algorithm. Slow processors meant low speed of convergence and a slow adaptation. There are a lot of adaptive algorithms that can fur fill the job that a smart antenna system has to accomplish. The main purpose of this paper is however to present the main advantages of creating a MATLAB GUI (Graphical User Interface) in order to study these algorithms. The GUI described studies 62 adaptive algorithms, some described in literature, some propose by the authors. We will make a short description of the LMS (Least Mean Squares Algorithm), the APA (Affine Projection Algorithm) and the GASSAPA (Gradient Adaptive Scalar Step Size Affine Projection Algorithm) and compare them with the use of the graphical interface.

Generalized Scalar PWM Algorithm for VSI Fed Induction Motor Drives with Reduced Complexity

This paper presents a simple and novel generalized pulse width modulation (GPWM) algorithm for voltage source inverter fed induction motor drives. The classical space vector approach requires angle and sector information for the calculation of switching times, which increases the complexity of the PWM algorithm. Hence, to reduce the complexity, the proposed GPWM algorithm generates the modulating signals by using the instantaneous phase voltages only. In the proposed algorithm, a unique zero sequence signal is added to the instantaneous phase voltages in order to generate the modulating waveforms. By varying a constant in the zero sequence signal from 0 to 1, various PWM algorithms such as space vector PWM (SVPWM) and discontinuous PWM (DPWM) algorithms are generated. Moreover, a simple overmodulation algorithm is also presented in this paper. Thus, the proposed GPWM algorithm generates all possible PWM algorithms in the entire modulation region. To validate the proposed algorithm, several simulation and experimental results are presented and compared. The results show the best agreement with the published work.