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20th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC)

作者： Park, Jong-Woon Lim, Dong-Kuk Univ Ulsan Dept Elect Elect & Comp Engn Ulsan South Korea

ISBN: (数字)9781665468336

ISBN: (纸本)9781665468336

This paper investigates the best design of IPMSM for eco-friendly ships using a hybrid ABC-SVM algorithm (HAS). HAS is a multimodal optimization method capable of exploring several optimal solutions. HAS enhances navigation capability by combining the existing Artificial Bee Colony algorithm (ABC) with Support Vector Machine (SVM). In addition, hybridization with Simplex enables accurate and quick convergence on neighbor optimization at pointers discovered in ABC. In two test functions, the higher performance of the proposed algorithm is tested with conventional ABC, and the algorithm is applied to the optimal design of the IPMSM for the eco-friendly ship.

关键词： Electromagnetic analysis Eco-friendly ship Motor optimization optimization algorithm Permanent magnet motors

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optimization-based reference calculation for Modular Multilevel Converters in balanced and unbalanced network conditions 23

Optimization-based reference calculation for Modular Multile...

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23rd European Conference on Power Electronics and Applications (EPE ECCE Europe)

作者： Spier, Daniel Westerman Prieto-Araujo, Eduardo Lopez-Mestre, Joaquim Gomis-Bellmunt, Oriol Control Intelligent Energia Coop CINERGIA Carrer Can Baletes 7 Argentona 08310 Spain Univ Politecn Cataluna CITCEA UPC Avinguda Diagonal 647 Barcelona 08028 Spain

ISBN: (纸本)9789075815375

The paper addresses an optimization-based algorithm to calculate the references of the Modular Multi-level Converter (MMC) during normal and constrained scenarios (when the prioritization of quantities is required). The optimization problem prioritizes to satisfy the positive- and negative-sequence active and reactive current set-points demanded by the Transmission System Operator (TSO) through the corresponding grid code. If the TSO's requirements are achieved, the algorithm minimizes the arm impedances losses. Otherwise, it attempts to reduce the error between the current components and the TSO's current set-points. The optimization-based current reference calculation is derived based on the steady-state equations of the MMC, considering the maximum currents that can flow through the MMC's arms, the maximum and minimum arm applied voltages and the maximum sub-module capacitor's voltage. Simulation in the time-domain have been conducted and the results indicate that this method can be potentially employed to calculate the converter's references during both normal and faulted conditions.

关键词： Modular Multilevel Converters (MMC) HVDC optimization algorithm

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Aerodynamic Shape optimization for Delaying Dynamic Stall of Airfoils Using Cokriging Regression

Aerodynamic Shape Optimization for Delaying Dynamic Stall of...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Raul, Vishal Leifsson, Leifur Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

The dynamic stall phenomenon produces adverse aerodynamic loading, which negatively affects the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides a practical approach for delaying and mitigating dynamic stall characteristics without the addition of an auxiliary system. A typical ASO investigation requires multiple evaluations of accurate but time-consuming computational fluid dynamics (CFD) simulations. In the case of dynamic stall, unsteady CFD simulations are required for airfoil shape evaluation;combining it with high-dimensions of airfoil shape parameterization renders the ASO investigation computationally costly. In this study, metamodel-based optimization (MBO) is proposed using the multifidelity modeling (MFM) technique to efficiently conduct ASO investigation for computationally expensive dynamic stall cases. MFM methods combine data from accurate high-fidelity (HF) simulations and fast low-fidelity (LF) simulations to provide accurate and fast predictions. In particular, Cokriging regression is used for approximating the objective and constraint functions. The airfoil shape is parameterized using six PARSEC parameters. The objective and constraint functions are evaluated for a sinusoidally oscillating airfoil with the unsteady Reynolds-averaged Navier-Stokes equations at a Reynolds number of 135,000, Mach number of 0.1, and reduced frequency of 0.05. The initial metamodel is generated using 220 LF and 20 HF samples. The metamodel is then sequentially refined using the expected improvement infill criteria and validated with the normalized root mean square error. The refined metamodel is utilized for finding the optimal design. The optimal airfoil shape shows higher thickness, larger leading-edge radius, and an aft camber compared to baseline (NACA 0012). The optimal shape delays the dynamic stall occurrence by 3 degrees and reduces the peak aerodynamic coefficients. The performance of the MFM method is also co

关键词： Aerodynamic Shape optimization NACA 0012 Computational Fluid Dynamics Reynolds Averaged Navier Stokes Airfoil Geometry Leading Edges Lift Coefficient Richardson Extrapolation Vortices optimization algorithm

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Application of grey system theory to phosphorite sinter process: From modeling to control

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ASIAN JOURNAL OF CONTROL 2021年第1期23卷 13-22页

作者： Toktassynova, Nigina Fourati, Hassen Suleimenov, Batyrbek Satbayev Univ Dept Automat & Control Alma Ata Kazakhstan Univ Grenoble Alpes GIPSA Lab F-38400 Grenoble France

The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of phosphorite ore sintering is to regulate the parameters of the process to obtain a high quality sinter. The parameter clearly responsible for sinter quality is the temperature in the wind box. Therefore, in order to solve the control task, it is necessary to predict the highest temperature of the charge (also known as the burn through point (BTP)). In this paper, the theory of grey systems is used as a predictive model, which makes it possible to obtain an adequate model that uses a small number of initial samples of real temperature data. Based on the grey model GMC(1,n) a new optimal model is presented, which is constructed by using optimization algorithm. Optimal model predicts the BTP, and to establish an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the "particle swarm" algorithm.

关键词： burn through point control structure grey system optimization algorithm predictive model sinter process

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Global Steering for Control Moment Gyroscope Clusters Using Heuristic Variable Search Techniques

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JOURNAL OF SPACECRAFT AND ROCKETS 2021年第4期58卷 972-983页

作者： Papakonstantinou, Charalampos Lappas, Vaios J. Schaub, Hanspeter Kostopoulos, Vassilis Univ Patras Dept Mech Engn & Aeronaut Rion 26504 Greece Univ Patras Rion 26504 Greece Univ Patras Appl Mech & Vibrat Lab Rion 26504 Greece Univ Colorado Colorado Ctr Astrodynam Res Aerosp Engn Sci Dept Boulder CO 80303 USA

This paper addresses the problem of singularity avoidance in a four-control-moment-gyroscope cluster as used for the attitude control of a satellite. A global search algorithm is developed that adjusts the null motion added upon the singularity robust inverse steering law. Its principal characteristic is that it uses global information gathered from the whole maneuver, compared to most conventional techniques that consider only some local information, near the current gimbal configuration for the optimization. The method is implemented using a ternary tree structure, and a heuristic algorithm optimizes a cost function that depends on the manipulability index, the time spent in the vicinity of singularity, the quaternion error, and the gimbal rates. Specific measures are taken to decrease the execution time of the algorithm, even for long maneuvers, without the need of a visit histogram. In addition, the tuning of only two variables can drastically change the execution time and the computational resources needed. The numerical simulation used to evaluate the algorithm indicates that the elliptic singularity can sufficiently be avoided and the algorithm drives the system fast away from the singularity with an overall performance improvement.

关键词： Control Moment Gyroscope Quaternions Singularity Avoidance Steering Laws Search algorithm Satellites Histograms Numerical Simulation optimization algorithm Yaw Polynomial Interpolation

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Hybrid localization scheme using K-fold optimization with machine learning in WSN

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第12期35卷

作者： Yadav, Preeti Sharma, Subhash Chandra Rishiwal, Vinay IIT Roorkee Cloud Comp & Wireless Sensor Lab SRE Campus Saharanpur Uttar Pradesh India MJP Rohilkhand Univ Bareilly Uttar Pradesh India

Node localization technology can identify and track nodes, making observing data more relevant;for example, information received at the sink node would be useless to the client if node localization data from the sensor region were not included. Localization is described as determining the location of unknown sensor nodes named destination nodes applying the recognized location of anchor nodes based on measurements such as time difference of occurrence, time of occurrence, angle of occurrence, triangulation, and maximum probability. The purpose of node localization is to assign coordinates points to all sensor nodes arbitrarily put in the monitoring region and have an unknown location. Localization of nodes is essential to account for the cause of events that help group sensor querying, routing, and network coverage. In this paper, data transmission among the nodes is done by comparing the received signal strength indicator (RSSI) value with the supervised learning value. If the RSSI value is less than the supervised learning value, the data transmission takes place;else, no transmission. This paper proposes a hybrid localization scheme that effectively uses K-fold optimization with supervised learning and gives good results for distance error and RSSI/energy efficiency. The proposed scheme can effectively detect the optimal path for data transmission, node localization for the destination, and overall performance enhancement using threshold decision making.

关键词： localization machine learning optimization algorithm RSSI RTT WSN

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HFSA: hybrid feature selection approach to improve medical diagnostic system

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PEERJ COMPUTER SCIENCE 2025年 11卷 e2764-e2764页

作者： Rabie, Asmaa H. Aldawsari, Mohammed Saleh, Ahmed I. Saraya, M. S. Rashad, Metwally Mansoura Univ Fac Engn Comp & Control Syst Engn Dept Mansoura Egypt Prince Sattam Bin Abdulaziz Univ Coll Engn Wadi Alddawasir Comp Engn & Informat Dept Al Kharj Saudi Arabia Benha Univ Fac Comp & Artificial Intelligence Banha Egypt

Thanks to the presence of artificial intelligence methods, the diagnosis of patients can be done quickly and accurately. This article introduces a new diagnostic system (DS) that includes three main layers called the rejection layer (RL), selection layer (SL), and diagnostic layer (DL) to accurately diagnose cases suffering from various diseases. In RL, outliers can be removed using the genetic algorithm (GA). At the same time, the best features can be selected by using a new feature selection method called the hybrid feature selection approach (HFSA) in SL. In the next step, the filtered data is passed to the naive Bayes (NB) classifier in DL to give accurate diagnoses. In this work, the main contribution is represented in introducing HFSA as a new selection approach that is composed of two main stages;fast stage (FS) and accurate stage (AS). In FS, chi-square, as a filtering methodology, is applied to quickly select the best features while Hybrid optimization algorithm (HOA), as a wrapper methodology, is applied in AS to accurately select features. It is concluded that HFSA is better than other selection methods based on experimental results because HFSA can enable three different classifiers called NB, K-nearest neighbors (KNN), and artificial neural network (ANN) to provide the maximum accuracy, precision, and recall values and the minimum error value. Additionally, experimental results proved that DS, including GA as an outlier rejection method, HFSA as feature selection, and NB as diagnostic mode, outperformed other diagnosis models.

关键词： Feature selection Diagnosis NB classifier optimization algorithm Diseases Artificial intelligence Machine learning Filter methods Wrapper methods Healthcare

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Modeling and Control of Irrational Fractional-Order System and Its Block Diagram Simulation 34

Modeling and Control of Irrational Fractional-Order System a...

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34th Chinese Control and Decision Conference (CCDC)

作者： Chen, Lanfeng Xue, Dingyu Cui, Xinshu Shenyang Normal Univ Coll Phys Sci & Technol Shenyang 110034 Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China

ISBN: (纸本)9781665478960

The use of fractional-order to describe an actual system can better reveal its essential characteristics and its behavior. The description and analysis of an irrational fractional-order system are more complicated than that of a rational fractional-order system. To solve this difficulty, this paper studies its system identification and controller design for the characteristics of such systems. Firstly, based on the frequency domain response data of these systems, combined with the optimization algorithm to realize the rationalization of them, the curves fitting are used to illustrate the correctness and effectiveness of the identification algorithm. Then, based on the identified rational models, the optimum controllers are designed. Step response comparison shows that the performance of fractional-order controllers is superior to that of traditional integer-order controllers. Finally, through the block diagram implementation, the effectiveness and correctness of the fractional-order controller design are explained.

关键词： irrational fractional-order system frequency domain response data optimization algorithm optimum controllers block diagram

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A Novel Data-Driven Method to Estimate Invisible Solar Power Generation: A Case Study in Taiwan 58

A Novel Data-Driven Method to Estimate Invisible Solar Power...

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58th IEEE/IAS Industrial and Commercial Power Systems Technical Conference Asia (IEEE I and CPS Asia)

作者： Thi Bich Phuong Nguyen Wu, Yuan-Kang Manh-Hai Pham Natl Chung Cheng Univ 168 Univ Rd Chiayi 62102 Taiwan Elect Power Univ 235 Hoang Quoc Viet Rd Hanoi Vietnam

ISBN: (纸本)9781665409186

As the penetration of photovoltaic (PV) solar generation increases, numerous residential and commercial solar PV systems without meters are being installed. The majority of these systems, however, are not monitored by power system operators. Therefore, the uncertainty of net load owing to these invisible solar power generation will raise additional challenges for power system operation. To reduce the above-mentioned impact, this work proposes a novel method to estimate the total solar power generation in a large region from a small representative subset. The proposed method is capable of capturing all relevant information that assists in the identification of representative subsets. Moreover, different optimization algorithms are utilized and evaluated to select the optimal number of clusters and representative subsets. As a case study, the power generation of 166 PV sites in Taiwan was collected and analyzed. The proposed method demonstrates a significant improvement in estimating the aggregated power generation compared to other existing studies.

关键词： Photovoltaic (PV) Invisible Solar Power Behind-the-Meter data dimension reduction hybrid method optimization algorithm

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Automatic design of a high-image-quality augmented reality head-up display optical system with single optical engine and multi-focal planes based on smoothly stitched polynomial

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OPTICAL ENGINEERING 2025年第4期64卷

作者： Guo, Xiangxin Mu, Da Changchun Univ Sci & Technol Sch Phys & Optoelect Engn Changchun Peoples R China Changchun Univ Sci & Technol Photoelect Measurement & Control Technol Inst Changchun Peoples R China

Conventional augmented reality head-up display (AR-HUD) suffers from various issues, such as the single-source image corresponding to the single focal plane, difficult optimization design of special face shape, and low definition under a wide frame. We propose an AR-HUD imaging system design method based on a single image source, multi-focal plane architecture with dual free-form surfaces, enabling compatibility with arbitrary windshield geometries. First, Malus' law and the law of reflection are applied to solve the point cloud envelope distribution. Following field-of-view expansion under adjacent-domain continuity conditions, the data are fitted and characterized using a smoothly stitched polynomial (SSP) to construct the initial architecture. Finally, an optical path feedback iteration method is employed to optimize edge fields and determine the optimal fitting coefficients. Using this method, two AR-HUD spatial display layouts are designed: horizontal and vertical multi-focal plane configurations. Simulation results indicate that the proposed iterative algorithm achieves high optimization efficiency. Comparative analysis between SSP-characterized surfaces and traditional XY polynomial surfaces demonstrates significant improvements in edge-field modulation transfer function and grid distortion. These results further validate the feasibility and superiority of the proposed design framework.

关键词： geometric optics smoothly stitched polynomial optimization algorithm multi-focal plane display

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