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SSRN 2023年

作者： Ervan, Osman Temeltas, Hakan Department of Control and Automation Engineering Faculty of Electric and Electronics Istanbul Technical University Ayazaga Campus Sariyer Maslak Istanbul34469 Turkey

Three-dimensional (3D) point cloud registration is a fundamental process in the fields of computer vision and robotics. It enables the alignment and fusion of multiple point cloud datasets acquired from diverse viewpoints or distinct temporal instances. The rapid progress of 3D sensing technologies in 3D LiDAR sensors has led to the widespread availability of point cloud data across various applications, including robotics, autonomous navigation, object recognition, and cultural heritage preservation. Nevertheless, the inherent presence of noise, occlusions, and varying scales within acquired point clouds presents significant challenges in achieving precise registration. In this paper, we proposed MultI-LEvel coarSe-TO-fiNe rEgistration algorithm, referred to as MILESTONE. Geometric features of the points have been extracted using eigenvalue and eigenvector-based multi-level similarity metrics. During pairwise registrations, changing the input point cloud between source and target can impact the registration performance. To address this issue, we introduced a correspondence intersection search mechanism, which effectively overcomes this problem. The similarity percentage metric calculation procedure generates the probability of two correspondence pairs being an exact match. These robust tools enhance the quality of the coarse registration, not only in terms of accuracy but also in terms of time consumption. Finally, the results of the coarse registration are updated in the fine registration step, completing the coarse-to-fine registration pipeline. The contribution of this proposed method lies in the enhancement of coarse registration accuracy, coupled with a reduction in the time required for fine registration. Comprehensive experimentation confirms that the proposed algorithm yields favorable outcomes, encompassing a high rate of successful registration, precise rotation estimation, accurate translation estimation, efficient runtime, and notably, surpasses the cap

关键词： Nearest neighbor search

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On Solar Photovoltaic Parameter Estimation: Global Optimality Analysis and a Simple Efficient Differential Evolution Method

On Solar Photovoltaic Parameter Estimation: Global Optimalit...

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IEEE Conference on Decision and control

作者： Shuhua Gao Cheng Xiang Ming Yu Kuan Tak Tan Tong Heng Lee School of Control Science and Engineering Shandong University Jinan China Department of Electrical and Computer Engineering National University of Singapore Singapore Power Automation Pte Ltd Singapore Engineering Cluster Singapore Institute of Technology Singapore

The literature presents a vast array of advanced metaheuristic methods for photovoltaic parameter estimation. However, the focus of this study is not to introduce another new method into this already crowded field. Instead, we examine two important but often overlooked questions: (i) are existing results globally optimal, and (ii) can a simpler method achieve comparable performance. We conduct case studies using two widely used I-V curve datasets. To address the first issue, we develop a branch and bound algorithm that, despite its sluggishness, either certifies the global minimum or provides a tight upper bound. These values serve as useful benchmarks for fair metaheuristic evaluation and further development. To answer the second question, our extensive examination and comparison surprisingly reveal that a basic differential evolution (DE) algorithm can achieve the certified global minimum or obtain the best known result. Additionally, the DE algorithm's runtime is much shorter than that of current state-of-the-art metaheuristic methods, making it a great choice for time-sensitive applications. This remarkable finding suggests that using increasingly complex metaheuristics in ordinary PV parameter estimation problems might be unnecessary. Finally, we discuss the implications of these outcomes and propose the simple DE method as the premier choice for industrial applications.

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Designing of A Plastic Garbage Robot With Vision-Based Deep Learning Applications

Designing of A Plastic Garbage Robot With Vision-Based Deep ...

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2023 International Conference on System Science and engineering, ICSSE 2023

作者： Thanh, Le Tien Lam, Le Hoang Nguyen, Thanh Nha Tran, Duc Thien Ho Chi Minh City University of Technology and Education Automation Control Department Ho Chi Minh City70000 Viet Nam Ho Chi Minh City University of Technology and Education Faculty of Electrical and Electronics Engineering Ho Chi Minh City70000 Viet Nam

ISBN: (纸本)9798350322941

To address the issue of plastic waste, a robot using deep learning technology for visual recognition to classify plastic waste has been developed. This system includes a 3DOF robot arm, a conveyor, a camera, an electrical cabinet, and a computer. The object detection component of the system is designed using transfer learning with a pre-trained YOLOv5 model to ensure the system operates in real time. Selecting the best model by evaluating and comparing the results of models trained using labeling by bounding box and polygon methods. Then, the real-world coordinates for the origin of the robot arm are determined by utilizing matrices obtained from MATLAB through chessboard images. The computer processes the data and transmits commands to the robot arm system and conveyor, which is controlled by a PLC and 3 different Servo Drivers, for object sorting on the conveyor. The best-performing model has a Precision of 92.1% and a Recall of 87.3%, and the success rate of picking up an object is 91.5%. While the experimental results indicate complete stability in inter-device connectivity, implementing it would necessitate hardware improvements to leverage its potential. © 2023 IEEE.

关键词： Deep learning

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Efficiency Enhancement of The PV System Through Reconfiguration Strategies Under Non-Uniform Irradiance Conditions

Efficiency Enhancement of The PV System Through Reconfigurat...

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International Conference on Electrical engineering, Computer Science and Informatics (EECSI)

作者： Salim Ahmed Ali Ahmed R. Ajel Safaa A. Ghadhban Department of Electrical Power Engineering Techniques Electrical Engineering Technical College Middle Technical University Baghdad Iraq Department of Medical Devices Techniques Engineering Electrical Engineering Technical College Middle Technical University Baghdad Iraq Department of Control & Automation Techniques Engineering Electrical Engineering Technical College Middle Technical University Baghdad Iraq

Solar photovoltaic (PV) arrays experience a significant surge in power losses due to Partially Shaded Conditions (PSCs). The presence of clouds, shadows from tall structures, trees, chimneys, and bird droppings can lead to these PSCs. When PV modules are shaded, they go into reverse bias, causing small hotspots to form and increase the system's overall temperature. To mitigate this issue, bypass diodes can be connected antiparallel to the PV modules, although this leads to multiple peaks in the I-V and P-V characteristics. Along with the challenges presented by hotspots, mismatch losses between different modules further, reduce the electricity output of a PV array. The research in focus is designed to evaluate, model, simulate, and analyze the effectiveness of several 4x4 PV array configurations operating under diverse PSCs. Topologies such as series-parallel, bridge-link, honeycomb, and total cross-tied (TCT) are investigated, along with different partial shading patterns like corners, centers, ends, L-shapes, frames, random, and diagonals. These investigations are grounded on the technical specifications of a 130-watt PV module.

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Asynchronous State Estimator Design for Markov Switched Systems with Incomplete Probabilities and Redundant Channels

Asynchronous State Estimator Design for Markov Switched Syst...

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第42届中国控制会议

作者： Haiyang Chen Fangzheng Gao Xueyi Mao School of Control Science and Engineering Tiangong University School of Automation Nanjing Institute of Technology Publicity Department Nanjing Communications Institute of Technology

This paper is concerned about the H∞ asynchronous state estimator design for Markov switched systems(MSSs)with incomplete transition probabilities and redundant channels.A hidden Markov chain(HMC) is introduced to characterize the asynchronous degree between the state estimator mode and the system *** an asynchronous full-order state estimator is devised for the ***,by Lyapunov functional and stochastic analysis,new criteria are derived such that the augmented system consisting of the target system and state estimator is H∞ stochastically finite-time *** that,with matrix decoupling technique,a design algorithm is obtained in form of linear matrix inequalities(LMIs).Finally,the practical one-link robotic manipulator is utilized to validate the developed results.

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Computationally Efficient Core Losses Calculation and Thermal Evaluation Using the VBR-Based Finite Element Model of Induction Motors

Computationally Efficient Core Losses Calculation and Therma...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Zahra Valipoor Hossein Nejadi Koti Nabeel A. O. Demerdash Electrical and Computer Engineering Department Marquette University Milwaukee USA Motion Control Team Rockwell Automation Inc. Mequon USA

Accuracy of the simulation results obtained from the FEA analysis of electric motors is highly dependent on the quality of the motor performance metrics such as motor steady state temperatures and losses. In addition such FEA analysis is typically computationally burdensome and demanding. Improving the computational burden and accuracy of core losses calculation and thermal evaluation in Time-Stepping Finite Element (TS-FE) models of induction motors is addressed in this paper. The Virtual Blocked Rotor (VBR)-based Time-Stepping Finite Element (TS-FE) technique is utilized to mitigate the numerical transient response of the induction motor FE model. The motor core losses have been calculated through the harmonic based core loss calculation that assumes variable loss coefficients as a function of magnetic flux density. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components.

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Research on the Flux-weakening Capability of the Reverse-salient Permanent Magnet Synchronous Motor

Research on the Flux-weakening Capability of the Reverse-sal...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Xiaokun Zhao Cheng Zhang Weinan Wang Baoquan Kou Liangkuan Zhu College of Computer and Control Engineering Northeast Forestry University Harbin China Department of Electrical and Automation Harbin Institute of Technology Harbin China

Permanent magnet synchronous motors (PMSMs) offer the benefits of high torque density and a superior power factor. Nevertheless, the challenge lies in the inherent difficulty of adjusting the permanent magnet flux. To address this issue, this paper analyzes the influence of electromagnetic parameters on the constant-power speed range (CPSR). First, the analysis focuses on the influence of d-axis inductance and saliency ratio, aiming to establish a design method for achieving a wide CPSP in PMSMs. Second, based on the electromagnetic parameter requirements, a reverse-salient PMSM is proposed and its working principle is explained. Finally, the electromagnetic characteristics, including torque and the CPSP, are determined through the application of the finite element method (FEM). The obtained results confirm that the reverse-salient PMSM achieves a CPSP of 7:1, thus validating the accuracy of the theoretical analysis.

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Performance Enhancement of The PV Array Based on Hybrid Configuration Under Variable Irradiance Conditions

Performance Enhancement of The PV Array Based on Hybrid Conf...

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Vocational Education and Electrical engineering, International Conference on

作者： Salim A. Ali Ahmed R. Ajel Safaa A. Ghadhban Department of Electrical Power Engineering Techniques Electrical Engineering Technical College Middle Technical University Baghdad Iraq Department of Medical Devices Techniques Engineering Electrical Engineering Technical College Middle Technical University Baghdad Iraq Department of Control & Automation Techniques Engineering Electrical Engineering Technical College Middle Technical University Baghdad Iraq

The study investigates the challenges posed by" partial shading conditions" (PSCs) on a performance and efficiency of solar photovoltaic (PV) systems. The primary goal is to find the best photovoltaic array setup to optimize power output while reducing efficiency losses caused by mismatching. The researchers evaluate various PV configurations such as Series (S), Series-Parallel (SP), Total Cross Tied (TCT), Bridge Linked (BL), Honey Comb (HC), and a hybrid of TCT and BL called TCT-BL, focusing on a 4x4 array layout. Six different shading patterns are examined, including diagonal, "short and narrow", "short and wide", "long and narrow", "long and wide", and random. Based on simulations using Matlab/Simulink and a 130W PV module model, the study suggests that the TCT-BL configuration offers superior power generation, efficiency, and reduced mismatching loss compared to other configurations under most PSCs examined.

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite Systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Solar Radiation Forecasting Based on Random Forest and XGBoost 7

Solar Radiation Forecasting Based on Random Forest and XGBoo...

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7th International Conference on Green Technology and Sustainable Development, GTSD 2024

作者： Nguyen, Nhat-Truong Tuong Dao, Thai Cat Tuyen Nguyen, Le Nhut Nguyen, Thanh-Dat Le, Minh-Vuong French, Isobel Timothea Doan, Van-Tuong Kim Vo, Van Hoang Tran, Nghi C. Pham, Duc-Hung Nguyen, Van-Trung Ho Chi Minh City University of Technology and Education Department of Renewable Energy Viet Nam Ho Chi Minh City Industry and Trade College Department of Control Engineering and Automation Viet Nam LILAMA2 International Technology College Dongnai Viet Nam Institute of Cognitive Neuroscience National Central University Taiwan College of Information and Communication Technology Can Tho University Viet Nam Hung Yen University of Technology and Education Faculty Electrical and Electronic Engineering Viet Nam

ISBN: (纸本)9798350386073

Renewable energy offers a viable alternative to depleting fossil fuels, contributing to global warming and greenhouse gas emissions. Thus, solar energy is widely favored as a renewable energy source. However, the output power of solar systems is unstable and is highly dependent on environmental circumstances such as radiation, humidity, temperature, and wind. Therefore, accurately estimating solar radiation is crucial for successful integration of the solar system into existing electrical grid systems. In this study, two different machine learning models, XGBoost and Random Forest, were used to predict solar radiation data in Ho Chi Minh City, Vietnam. The results show that RMSE and MAE of the Random Forest model (61.09 and 24.37) is smaller compared to XGBoost (61.31 and 25.08). Regression value of the two models is close to 0.955. In summary, this paper demonstrates that these two machine learning algorithms effectively forecast solar radiation, with the Random Forest model showing better performance. © 2024 IEEE.

关键词： Solar irradiance

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