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Forecasting-Aided Graphical Learning for Robust State Estimation of Distribution System 1

8th Purple Mountain Forum on Smart Grid Protection and Control, PMF 2023

作者： Di, Cao Zhao, Junbo Hu, Jiaxiang Huang, Yuehui Huang, Qi Chen, Zhe Hu, Weihao University of Electronic Science and Technology of China Chengdu China Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269 United States State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems China Electric Power Research Institute Beijing China Department of Energy Technology Aalborg University Pontoppidanstraede 111 Aalborg Denmark

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

The forecasting of of pseudo-measurements play an important role in distribution system state estimation (DSSE). This paper proposes robust DSSE method based on forecasting-aided graphical learning method. The nodal power consumption models are first built to produce pseudo-measurements based on deep neural network. Then, the pseudo-measurements and real-time measurements are represented as a graph according to the topology of the distribution network, which are further processed by a graph attention network to capture the mapping relationship between the graphical measurements and the state variables based on the error modeling of pseudo-measurements. The robustness against anomalous measurements is achieved through the embedding of structural information of DN. The modeling of pseudo-measurements further enhance its robustness by guiding the formulation of edge weights of the graph neural network. Comparative tests are carried out on a IEEE 119-node system to demonstrate the effectiveness and robustness of the proposed method. © 2024, State Grid Electric Power.

关键词： Electric power distribution

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Coupled Transformed Induced Tensor Nuclear Norm for Robust Tensor Completion

Coupled Transformed Induced Tensor Nuclear Norm for Robust T...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Mengjie Qin Zheyuan Lin Minhong Wan Chunlong Zhang Jason Gu Te Li Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax

This study focuses on exploring the problem of low-rank tensor completion (LRTC), where the main challenge lies in accurately representing the inherent structures of the underlying data. Typical approaches exhibit either suboptimal performance due to the lack of suitable priors or combine many constraints, resulting in increased model complexity. In this paper, we propose a robust transformed t-SVD by utilizing the discrete cosine transform in conjunction with a unitary transformation matrix. Nonetheless, the t-SVD-based framework exhibits a deficiency in its capacity to flexibly explore diverse correlations across tensor modes. To address this issue, we employ the representation of the tensor as a series of multi-dimensional unfolding tensors, which fully capture the embedded structure in the original data. Moreover, on the basis of this tensor representation, we construct a transformed t-SVD method within the LRTC model and solve it by the alternating-direction method of multiplier (ADMM) approach. Extensive experiments demonstrate that the proposed model outperforms existing state-of-the-art methods.

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Design and Implementation of Neuro-Fuzzy Control Approach for Robot's Trajectory Tracking 7

Design and Implementation of Neuro-Fuzzy Control Approach fo...

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7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023

作者： Kiruba Sandou, D. Sunad Kumara, A.N. Choudhary, Binod Kumar Gurpur, Shashikala Sarishma Natrayan, L. Sivaramkumar, M. Manakula Vinayagar Institute of Technology Department of Robotics and Automation Pondicherry605107 India BGS Institute of Technology Department of Computer Science and Engineering Adichunchanagiri University Karnataka Mandya571448 India ARKA Jain University Department of Electrical and Electronics Engineering Jharkhand Jamshedpur832108 India Maharashtra Pune411014 India Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun India Saveetha School of Engineering SIMATS Department of Mechanical Engineering Tamilnadu Chennai602105 India Karpagam Academy of Higher Education Department of EEE Tamiinadu Coimbatore India

ISBN: (纸本)9798350340600

Achieving precise trajectory tracking while minimizing errors, reducing settling time, and curbing overshoot presents a significant challenge in the domain of robot-manipulator control. In response, this paper proposes a novel controller design for robot manipulators, incorporating two distinct approaches: a conventional fuzzy controller and an advanced Neuro-Fuzzy controller. These controllers are tailored to elevate trajectory tracking performance by simultaneously optimizing time characteristics in robot manipulator responses. To assess their efficacy, a range of test scenarios is devised, encompassing different trajectory types, including linear and nonlinear paths. Upon comparative analysis, the results highlight an intriguing contrast: while the fuzzy controller exhibits higher maximum overshoot and longer settling times in the robot's response, the Neuro-Fuzzy controller consistently demonstrates superior performance. The comprehensive error analysis such as Integral Square Error (ISE) and Integral Absolute Error (IAE) further underscores the capability of the Neuro-Fuzzy-based robot manipulator in delivering trajectory tracking precision. This study contributes to the advancement of trajectory control techniques for robot manipulators, paving the way for enhanced automation and performance across various applications. © 2023 IEEE.

关键词： Controllers

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Automated Arabic Text Classification Using Hyperparameter Tuned Hybrid Deep Learning Model

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computers, Materials & Continua 2023年第3期74卷 5447-5465页

作者： Badriyya B.Al-onazi Saud S.Alotaib Saeed Masoud Alshahrani Najm Alotaibi Mrim M.Alnfiai Ahmed S.Salama Manar Ahmed Hamza Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Prince Saud AlFaisal Institute for Diplomatic Studies Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The text classification process has been extensively investigated in various languages,especially *** classification models are vital in several Natural Language Processing(NLP)*** Arabic language has a lot of *** instance,it is the fourth mostly-used language on the internet and the sixth official language of ***,there are few studies on the text classification process in Arabic.A few text classification studies have been published earlier in the Arabic *** general,researchers face two challenges in the Arabic text classification process:low accuracy and high dimensionality of the *** this study,an Automated Arabic Text Classification using Hyperparameter Tuned Hybrid Deep Learning(AATC-HTHDL)model is *** major goal of the proposed AATC-HTHDL method is to identify different class labels for the Arabic *** first step in the proposed model is to pre-process the input data to transform it into a useful *** Term Frequency-Inverse Document Frequency(TF-IDF)model is applied to extract the feature ***,the Convolutional Neural Network with Recurrent Neural Network(CRNN)model is utilized to classify the Arabic *** the final stage,the Crow Search Algorithm(CSA)is applied to fine-tune the CRNN model’s hyperparameters,showing the work’s *** proposed AATCHTHDL model was experimentally validated under different parameters and the outcomes established the supremacy of the proposed AATC-HTHDL model over other approaches.

关键词： Hybrid deep learning natural language processing arabic language text classification parameter tuning

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Silicon Photonics Foundry Fabricated, Slow-Light Enhanced, Low Power Thermal Phase Shifter

arXiv

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arXiv 2024年

作者： Chen, Alexander Zhang, Meng Crowley, Daniel Gangi, Nicholas Begović, Amir Huang, Zhaoran Rena Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States

In this research, we developed a low-power silicon photonics foundry-fabricated slow-light thermal phase shifter (SLTPS) where the slow-light (SL) effect is achieved using an integrated Bragg grating (BG) waveguide. Heating the grating induces a red shift in the transmission spectrum, leading to an increased group index ng during operation, which facilitates a further reduction in the voltage needed for a π phase shift, i.e. Vπ. Additionally, we investigated a compact Mach-Zehnder Interferometer (MZI) that incorporates the SLTPS in both arms with a phase shifter length of 50 µm. A detailed theoretical analysis was conducted to address the non-idealities of the SL-MZI due to uneven optical power splitting and unbalanced loss in the two MZI arms. The Vπ and power consumption for a π phase shift (Pπ) of the SL-MZI were quantified for operation in the slow light regime, demonstrating a Vπ of 1.1 V and a Pπ of 3.63 mW at an operational wavelength near the photonic band edge. The figure of merit (FOM) Pπ × τ is commonly used to assess the performance of thermal optical switches. The SL-MZI in this work has achieved a low Pπ ×τ of 5.1 mW µs. Insertion loss of the SL-MZI ranges from 1.3 dB to 4.4 dB depending on the operation wavelength, indicating a trade-off with the Vπ reduction. Copyright © 2024, The Authors. All rights reserved.

关键词： Slow light

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(Invited) Improved Thin Film Transistor Model Predicts TFT Operation in the THz Range 242

(Invited) Improved Thin Film Transistor Model Predicts TFT O...

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242nd ECS Meeting

作者： Shur, Michael Liu, Xueqing Ytterdal, Trond Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Electronics of the Future Inc ViennaVA22181 United States Department of Electronic Systems Norwegian University of Science and Technology Trondheim7491 Norway

ISBN: (纸本)9781607685395

Novel materials such as ZnO, InGaZnO, AMO-CNT, and organic materials and improved fabrication processes dramatically enhanced the achieved and projected thin film transistor (TFT) performance. The effective field-effect mobility of metal oxide TFT materials has reached values comparable to those for short-channel Si CMOS. We report on an improved compact model based on the RPI TFT model, the unified charge control model (UCCM), and the multi-segment TFT compact model. This improved model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-Trivial capacitance dependence on the gate bias. The application of this new TFT model to the analysis of the TFT response showed that a TFT complementary inverter using the phase-matched THz signal feeding should yield a very sensitive detection of THz radiation impinging on a short channel TFT. © 2022 ECS-The Electrochemical Society.

关键词： Thin film transistors

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Robust STL Control Synthesis under Maximal Disturbance Sets

Robust STL Control Synthesis under Maximal Disturbance Sets

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IEEE Conference on Decision and Control

作者： Joris Verhagen Lars Lindemann Jana Tumova Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Thomas Lord Department of Computer Science University of Southern California Los Angeles CA USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This work addresses maximally robust control synthesis under unknown disturbances. We consider a nonlinear system, subject to a Signal Temporal Logic (STL) specification and jointly synthesize the maximal possible disturbance bounds and the corresponding controllers that ensure the STL specification is satisfied under these bounds. Many works have considered STL satisfaction under given bounded disturbances yet, to the authors’ best knowledge, this is the first work that aims to maximize the permissible disturbance set and find corresponding maximally robust controllers. We, therefore, introduce disturbance robustness as a model-based robustness metric for STL planning and control synthesis. We extend the notion of disturbance-robust semantics for STL, which is a property of a specification, dynamical system, and controller, and provide an algorithm for maximally robust controllers satisfying an STL specification using Hamilton-Jacobi reachability. We show its soundness and provide a simulation example with an Autonomous Underwater Vehicle (AUV).

关键词： Measurement Robust control Heuristic algorithms Semantics Control systems Robustness Planning Logic Dynamical systems Nonlinear systems

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Investigation of the Impact of Height and Bandwidth on Path Loss Exponent of 5G FR1 Wireless Networks at 800, 3500, and 5900 MHz 2

Investigation of the Impact of Height and Bandwidth on Path ...

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Imam-Fulani, Yusuf Olayinka Faruk, Nasir Usman, Aliyu D. Abdulkarim, Abubakar Tekanyi, Abdoulie M.S Yaro, Abdulmalik S. Alozie, Emmanuel Garba, Salisu Adewole, Kayode S. Oloyede, Abdulkarim A. Sowande, Olugbenga A. Abdullahi Baba, Bashir Musa, Abdulwaheed Imoize, Agbotiname Lucky Adediran, Yinusa A. Olagunju, Hawau I. Taura, Lawan S. University of Ilorin Department of Telecommunication Science Ilorin Nigeria Ahmadu Bello University Department of Electronics and Telecommunication Engineering Zaria Nigeria Sule Lamido University Department of Information Technology Kafin Hausa Nigeria Sule Lamido University Directorate of Information and Communication Technology Kafin Hausa Nigeria Ahmadu Bello University Department of Electrical Engineering Zaria Nigeria Kampala International University Department of Electrical and Telecommunication Engineering Kampala Uganda University of Hradec Králové Faculty of Informatics and Management Department of Informatics and Qualitative Methods Hradec Králové Czech Republic Sule Lamido University Department of Software Engineering Kafin Hausa Nigeria University of Ilorin Department of Computer Science Ilorin Nigeria Kwara State University Department of Electrical and Computer Engineering Malete Nigeria University of Johannesburg Institute for Intelligent Systems Johannesburg South Africa University of Lagos Department of Electrical and Electronics Engineering Lagos Nigeria Ruhr University Institute of Digital Communication Department of Electrical Engineering and Information Technology Bochum Germany University of Ilorin Department of Electrical and Electronics Engineering Ilorin Nigeria Sule Lamido University Department of Physics Kafin Hausa Nigeria

ISBN: (纸本)9798350358834

5G communication systems provide an end-to-end wireless connection to billions of users and devices across the globe. The quality of signals received during radio communication is notably influenced by the behavior of the radio propagation channel. A major parameter used in characterizing this channel is the Path Loss Exponent (PLE). Several works that have estimated and analyzed the PLE mostly considered the effect of distance and carrier frequency. However, the effect of base station antenna height and channel bandwidth on the PLE for 5G networks have not been adequately considered. To address this, the impact of antenna height of base station and channel bandwidth on the PLE within the 5G Frequency Range 1 (FR1) frequencies was investigated in this study, specifically at 800, 3500, and 5900 MHz. The licensed EDX Signal Pro software® with Cirrus high resolution global terrain and clutter data base was utilized to model, simulate and analyze the PLE for Kano City, Nigeria. Results showed that for the tested frequencies, an increase in either base station height or channel bandwidth leads to a significant reduction in the PLE. This study can be utilized by network planning engineers and the wireless research community to further improve network implementation and optimization toward understanding the behavior of signal propagation in 5G networks and beyond. © 2023 IEEE.

关键词： 5G mobile communication systems

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Compensation Control of PMSMs Based on a High-order Sliding Mode Observer with Inertia Identification

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Li, Ke Ding, Jie Sun, Xiaodong Lei, Gang Dianov, Anton Demidova, Galina Prakht, Vladimir Jiangsu University School of Electrical and Information Engineering Zhenjiang212013 China Jiangsu University Automotive Engineering Research Institute Zhenjiang212013 China University of Technology Sydney School of Electrical and Data Engineering NSW2007 Australia Wenzhou University Pingyang Institute of Intelligent Manufacturing Wenzhou325035 China ITMO University Faculty of Control Systems and Robotics Petersburg197101 Russia Ural Federal University Department of Electrical Engineering Ekaterinburg620062 Russia

This article proposes a new sliding mode control (NSMC) reaching law to improve the speed tracking and anti-interference performance of permanent magnet synchronous motors (PMSMs). The NSMC improves the sliding mode control (SMC) in approaching speed and reducing chattering. Firstly, considering that the external load interference will adversely affect the control system, a high-order sliding mode observer (HOSMO) is designed to observe the load torque, and the observed value is compensated to the output of the speed controller. Then, combined with the Landau algorithm, a variable adaptive gain algorithm is introduced to decrease the impact of inertia mismatch on the system control performance. The algorithm identifies the rotational inertia online, reduces the effect of load disturbance on the identification performance, and updates the identification results to the observation in processors and controllers. Experimental results show that the proposed control method reduces the speed and current fluctuations of the system when load torque and inertia vary and improves the system's robustness. © 2013 IEEE.

关键词： Permanent magnets

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A Dual-Band MIMO Monopole Antenna with Enhanced Isolation for Sub 6 GHz 5G Applications

A Dual-Band MIMO Monopole Antenna with Enhanced Isolation fo...

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2024 International Conference on Advances in electrical and Communication Technologies, ICAECOT 2024

作者： Hamrioui, Fatma Zohra Bouaza, Abdelmaoula Touhami, Rachida Yagoub, Mustapha C.E. Azrar, Arab Electronic Department 10 Rue des Frères OUDEK El Harrach Algiers16200 Algeria Usthb university Bp32 Instrumentation laboratory Electronics and Informatics faculty El Alia Bab Ezzouar Algiers Algeria University of Ottawa Element laboratory School of Electrical Engineering and Computer Science Ottawa Canada Institute of Electrical and Electronic Engineering University M'Hamed BOUGARA-Boumerdes Signals and Systems Laboratory Electronics Department Boumerdes Algeria

ISBN: (纸本)9798350353754

In this paper, a novel dual-band MIMO monopole antenna for 5G applications is presented. The proposed MIMO antenna is made up of two rings that are T-shaped, generating two distinguished bands: the N77 band and the 6 GHz 5G band. A Tshaped ground branch with a bottom slit is integrated into the ground plane to mitigate the mutual coupling at lower and higher operating bands by redistributing the current, thus improving the isolation enhancement. A reversed T-shaped grounded parasitic element with extra grounded parasitic elements on the partial ground is inserted on top of the substrate, between the MIMO elements. The grounded process is introduced by inserting two metallic vias in each branch of the parasitic element. These parasitic elements effectively reduce the coupling between the MIMO antennas by restricting the current to the respective antenna, thus improving the isolation at the higher band. To verify the design principle of the suggested MIMO antenna, this latter is manufactured and tested. It exhibits excellent impedance matching and high isolation characteristics, and a compact footprint of 29 mm × 42.5 mm. Thus, it is attractive for 5G MIMO systems. © 2024 IEEE.

关键词： Monopole antennas

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