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Research on low voltage traverse control strategy of DFIG system based on elite ant colony active disturbance rejection

Research on low voltage traverse control strategy of DFIG sy...

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2021 international conference on Electronic Information engineering and Computer Technology, EIECT 2021

作者： Zhao, Zefang Zhang, Jiamin College of Electrical and Information Engineering Beihua University Jilin132013 China

ISBN: (数字)9781510650510

ISBN: (纸本)9781510650503

To prevent the off-grid phenomenon of wind turbines caused by voltage sag and realize the low-voltage traverse operation of doubly-fed induction wind turbine (DFIG), the elite strategy ant colony algorithm was used as a parameter optimization mechanism in the active disturbance rejection control (ADRC) system of the doubly-fed induction wind turbine. To make doubly-fed motor active disturbance rejection system have self-learning ability, an ant colony algorithm with distributed search and parallel computing ability is added to make it have automatic parameter optimization ability. After the simulation analysis of common ADRC and ant colony optimization ADRC, it is shown that the ADRC can improve the ability of low voltage crossing of the system, effectively reduce the transient current on the rotor side, and has good dynamic performance and strong robustness. © 2021 SPIE.

关键词： Ant colony optimization

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An IoT-Driven Workers Health Monitoring System Utilizing LoRa Technology for Real-Time Vital Signs Collection, Tracking and Cloud-Based Data Logging at Industrial Entry Points

An IoT-Driven Workers Health Monitoring System Utilizing LoR...

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2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Kaur, Navjot Malik, Praveen Kumar Krishna, Gopal Kumar, Manoj Aluvala, Srinivas Singh, Parulpreet School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Uttaranchal Institute of Technology Uttaranchal University Uttarakhand Dehradun India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India School of Computer Science & Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798331527495

With the rapid rise of IoT tech., new possibilities have emerged in areas such as health monitoring, especially in industries that require OHS. Traditionally, workplace health monitoring took a reactive stance resolving any adverse health conditions whenever they arise. Nonetheless, given that there have been shifts in technology and operational practices, what was once impossible has now become realizable - and that is the implementation of systems that continuously perform health monitoring in real-time. Such systems offer a constant evaluation of the most important health parameters with the aim of detecting health problems and preventing related adverse events at the early stage. This is particularly important in the workplace where the physical demand and hazards related to the occupation are high. With the advent of IoT technologies, the way of health insight which was very mechanized and physical in nature has changed to an intact automation system. Such a shift is, however, not simply improvement of technologies but a great efficiency advancement in health management at workplaces. Because of the connection of the cloud technology, the health status information is kept, and tested in one place, and relevant superiors and medical professionals are provided with the information they require to act quickly. Within this setting, IoT oriented technologies develop systems that act as the first line of defense in ensuring minimal delay response time in case there are health adversities, active surveillance on worker's health is also achieved. This paper presents a comprehensive improvement of an existing product intended to solve such problems. It shows how the problem of safety in the workplace can be achieved easily. © 2025 IEEE.

关键词： Medical problems

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A Development of Aquatic Landscape Type of Drones for the Implementation for Future Technology

A Development of Aquatic Landscape Type of Drones for the Im...

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Advance computing and Innovative Technologies in engineering (ICACITE), international conference on

作者： J Jayashankari Satendra Sahu B Arunkumar Kanchan Yadav M Gokilavani A. Vijayaprabhu Department of Information Technology (ITE) Prince Shri Venkateshwara Padmavathy Engineering College TN Department of Mechanical Engineering (M & E) IES College of Technology Bhopal M.P India Department of Computer Science Engg Karpagam Academy of Higher Education Department of Electrical Engineering GLA University Mathura Department of Information Technology Nehru Institute of Engineering and Technology T.M.Palayam Tamil Nadu India Department of ECE m Siddharth institute of Engineering and Technology Puttur Andhra Pradesh India

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

Cutting-edge, cost-effective hardware components allow the development of vast automated underwater drone systems for marine uses. This talk focuses on the CORATAM along with HANCAD projects, covering key issues in organizing and speaking within networks of underwater drones. Our plan supports a novel approach: (i) adopting eclectic communication by outfitting some drones at long-range electronics while others hold shorter-range devices, and (iii) employing autonomous control for enhanced endurance and scaling. This approach ensures individual drones stay simple and cheap. Currently, we are currently engaged in the process of building 25 test drones using easily available components. The article dives into current hardware creates and the results of simulation-based studies where groups of as many as one thousand underwater drones successfully surveyed a 20 km -long location constantly for 24 hours. The results confirm the practicality of our approach in building a large-scale robotic underwater unmanned aircraft system that is simultaneously efficient and affordable.

关键词： Navigation Surveillance Buildings Autonomous aerial vehicles Hardware Security Aircraft manufacture

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Impact of Data Preprocessing on Wind Forecasting Using Machine Learning Techniques 4

Impact of Data Preprocessing on Wind Forecasting Using Machi...

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4th international conference on Power, control and computing Technologies, ICPC2T 2025

作者： Gaikwad, Nidhi Haribhau Mitra, Arghya Payal, Jangilwar Das, Soumyabrata Keshri, Ritesh kumar Department of Electrical Engineering VNIT Nagpur India

ISBN: (纸本)9798331530402

There is a high demand for renewable energy sources as non renewable energy sources are harmful to the environment due to its effects such as global warming. Among non renewable energy source, the wind energy is unpredictable in nature, making Its integration with the grid a concern. By accurately forecasting wind energy, the stability of the grid can be ensured. The aforementioned can be achieved with the help of Machine Learning (ML) techniques. This paper investigate four ML techniques Multiple Linear Regression, Support Vector Regression, Random Forest Regression, and Decision Trees which are utilized and compared based on the metrics such as root mean square error, mean square error, mean absolute error, and R2 for three different cases. Initially errors are calculated without data preprocessing and later with data preprocessing. It is observed that preprocessing reduces error. This paper also investigates the effect of different seasons on the errors generated by these ML techniques. For this research, data is taken from National Solar Radiance database (NSRD) over two year period from January 2018 to December 2019. © 2025 IEEE.

关键词： Multiple linear regression

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Emotion Detection in Bangla Music Lyrics Using Machine and Deep Learning Approaches

Emotion Detection in Bangla Music Lyrics Using Machine and D...

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international conference on electrical, Computer and Communication engineering (ECCE)

作者： Hassan Md. Sharfuddin Miraz Punom Acharjee Esha Chowdhury Tahmina Akter Mst. Sharmin Akter Sajib Tripura Tanjim Mahmud Dept. of CSE Port City International University Chittagong Bangladesh School of Electronics and Control Engineering Chang’an University Xi’an China Dept. of CSE Rangamati Science and Technology University Rangamati Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Music has a tremendous impact on human emotions. It may elicit a wide range of emotions, including happiness, enthusiasm, sadness, and rage. This connection between music and emotion has motivated researchers in the field of Music Information Retrieval to create systems for automatic emotion identification in music. The emotional content of a song is conveyed mostly through its lyrics. This research focuses on detecting emotions in Bangla music lyrics using ML and DL techniques. The dataset consists of 4000 Bangla song lyrics, categorized into four emotion classes: Sad, Happy, Romantic, and Relaxation. We employed Bangla Glove for feature extraction and utilized Random Oversampling to address class imbalance. Our study compares the performance of several ML models, including LightGBM, RF, KNN, DT, XGBoost, and SVM. Additionally, we explored DL approaches using ANN, CNN, LSTM, and BiLSTM. To further enhance the performance, we developed hybrid models combining CNN with LSTM, BiLSTM, and GRU, as well as GRU with BiLSTM. Among these models, the RF model achieved the highest accuracy of 0.786, demonstrating its superior capability in capturing complex emotional expressions in Bangla music lyrics. The results present the potential of an ensemble ML in advancing emotion detection from textual data, particularly in the context of Bangla music.

关键词： Radio frequency Support vector machines Deep learning Emotion recognition Electric potential Accuracy Bidirectional long short term memory Nearest neighbor methods Feature extraction Music information retrieval

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14th APCA international conference on automatic control and Soft computing, controlO 2020

14th APCA International Conference on Automatic Control and ...

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14th APCA international conference on automatic control and Soft computing, controlO 2020

ISBN: (纸本)9783030586522

The proceedings contain 75 papers. The special focus in this conference is on automatic control and Soft computing. The topics include: Prototyping and control of a conveyor belt: An educational experiment in mechatronics;direct power control of a doubly fed induction generator using a lyapunov based state space approach;model of a dc motor with worm gearbox;trajectory planning for landing with a direct optimal control algorithm;accelerated generalized correntropy interior point method in power system state estimation;your turn to learn – flipped classroom in automation courses;modeling of an elastic joint: An experimental setup approach;on the control models in the trajectory tracking problem of a holonomic mechanical system;lmi-based sliding mode controller design for an uncertain single-link flexible robot manipulator;control of bio-inspired multi-robots through gestures using convolutional neural networks in simulated environment;addendum to "seeking a unique view to control of simple systems";welding process automation of aluminum alloys for the transport industry: An industrial robotics approach;open hardware and software robotics competition for additional engagement in ece students - the robot@factory lite case study;engine labels detection for vehicle quality verification in the assembly line: A machine vision approach;mitigation of earthquake-induced structural pounding between adjoining buildings – state-of-the-art;prototyping of a low-cost stroboscope to be applied in condition maintenance: An open hardware and software approach;dynamic survey of a telecommunication tower by interferometric radar technique;motion-based design of semi-active tuned mass dampers to control pedestrian-induced vibrations in footbridges under uncertainty conditions;preface.

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AGC for the Power System with ESS Participant in Frequency Regulation

AGC for the Power System with ESS Participant in Frequency R...

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international conference on Power System Technology (POWERCON)

作者： Shun Ma Muyang Liu Yinjun Xiong Junru Chen College of Electrical Engineering Xinjiang University Xinjiang China

Facing the challenge of the degrading frequency stability of the power systems with a high penetration of renewable power, the energy storage systems (ESSs) with fast frequency control is developed. This paper proposing a novel automatic Generation control (AGC) that better coordinates the ESS and the traditional synchronous generations on frequency regulation to improve the frequency stability of the power system. The proposed AGC includes two advanced techniques, namely the adaptive decomposition of the Area control Error (ACE) signal that separate the fast and slow frequency control signals feeding to the ESSs and synchronous generations respectively via the Empirical Wavelet Transform (EWT) method, and a control signal reallocating method according to the frequency support index of each generation unit regulated by the AGC. The effectiveness of the proposed AGC technique is validated through a case study based on a single-area power system with three conventional units and two ESSs.

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Real-Time Anomaly Detection in Industrial Automation Using Generative Adversarial Networks 5

Real-Time Anomaly Detection in Industrial Automation Using G...

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5th IEEE international conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Changala, Ravindra Khan, Shamim Ahmad Kumar, Vijay Rani, V. Kanpur Dhilli, K. Raj, I. Infant Department of Cse Guru Nanak Institutions Technical Campus Hyderabad India Glocal School of Science & Technology Glocal University Department of Ece Uttar Pradesh India Department of Physics Graphic Era Hill University Dehardun India Graphic Era Deemed to be University Dehradun India Hindustan Institute of Technology and Science Department of Eee Chennai India Vignan's Institute of Engineering for Women Dept of Ece Visakhapatnam India K. Ramakrishnan College of Engineering Department of Cse Tamil Nadu Trichy India

ISBN: (纸本)9798350356236

The study presents the use of GANs in anomaly detection for real-time industrial automation. A new model is proposed and implemented in Python, taking into consideration the dual nature of the algorithm known as GANs, which work on a dual framework including a generator and a discriminator. The normal behavior of industrial automation must be generated by a generator;meanwhile, the discriminator distinguishes between normal and anomalous data. It would facilitate the effective identification of anomalies, through adversarial training, based on learning normal operational patterns in real time, with the advantage of being adaptable in very dynamic and complex industrial environments. The ability to be timely about intervention, given its real-time capability, significantly enhances such attributes as predictive maintenance, improved quality control, and safe and efficient operations. This has been found in the study that the right identification of anomalies will prevent expensive downtime and will be a sign of smooth industrial process. In the proposed GAN model, 99.12% accuracy is achieved compared with other approaches, such as DBN, AnoGAN, and BiGAN, with an impressive gap of 4.05%. Thus, superior performance indicates that GANs are robust and reliable for dealing with real-time industrial automation challenges. A critical characteristic of this Python implementation model is its adaptability, flexibility, and amenability to a practitioner in the industry as much as a researcher. Overall, this study further provides significant additions to the overall understanding of anomaly detection in an industrial setting with its demonstration capabilities toward the resiliency enhancement and efficiency potential in modern systems of industry through GAN applications. © 2025 IEEE.

关键词： Office automation

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Using Biped Robot on Knee Exoskeleton for Stair Climbing Assistance Analysis

Using Biped Robot on Knee Exoskeleton for Stair Climbing Ass...

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2021 international automatic control conference, CACS 2021

作者： Lan, Chien-Wu Lin, Shih-Sung Ku, Chi-Ting Chen, Bo-Sian Lo, Min-Fang Chien, Mu-Ching Department of Electrical and Electronics Engineering Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan Department of Computer Science and Information Engineering Chinese Culture University Taipei Taiwan Missile and Rocket Systems Research Division National Chung-Shan Institute of Science and Technology Taoyuan Taiwan

ISBN: (纸本)9781665444125

Exoskeleton worn on human body becomes a complex biomechatronic system, and how to analyze it is a difficult research topic. In this study, a biped robot is developed for the knee exoskeleton analysis. The biped robot has four degrees of freedom, and fabricated with smart servo and inertial measurement units, which can provide motions information of the biped robot. In addition, the biped robot is dangled on a well-designed hanger to perform motions without considering the balance condition of the robot during the motions. Therefore, the exoskeleton assistance quality can be analyzed by comparing the difference of motion information while the robot performs actions with and without wearing the exoskeleton. In this research, the assistance performance analysis for the stair climbing motion of the knee exoskeleton is considered, and the position, the angular velocity and the current variation are discussed. Finally, the ability of the biped robot for analyzing the knee exoskeleton is verified. © 2021 IEEE

关键词： Robots

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Efficient Centralised and Decentralised Gaussian Process Approaches for Online Tracking within Stone Soup

Efficient Centralised and Decentralised Gaussian Process App...

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international conference on Information Fusion

作者： Chenyi Lyu Xingchi Liu James Wright Jordi Barr Alasdair Hunter Lyudmila Mihaylova Department of Automatic Control & Systems Engineering University of Sheffield UK Scientific Computing Department Rutherford Appleton Laboratory Science and Technology Facilities Council UK Defence Science and Technology Laboratory UK

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper explores the application of centralised and distributed Gaussian process algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is on the innovative implementation of Gaussian process methods with learning hyperparameters and implementation with a factorised variance of the Gaussian kernel. The performance of the methods with different kernels was evaluated, not only with the Gaussian kernel. Extensive experiments with various kernel configurations demonstrate their importance in enhancing prediction accuracy and efficiency, especially in real-time tracking. The case studies with manoeuvring targets show significant advancements in tracking capabilities, particularly in wireless sensor networks, using optimised Gaussian process methods. This work advances Stone Soup’s capabilities and lays the groundwork for future investigations into adaptive Gaussian Process applications in tracking and sensor data analysis.

关键词： Wireless sensor networks Technological innovation Analytical models Target tracking Data analysis Gaussian processes Benchmark testing Real-time systems Data models Kernel

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