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检索条件"任意字段=6th International Conference on Electrical Engineering, Computing Science and Automation Control"

共 5993 条记录，以下是211-220 订阅

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Quadrotor Attitude control Under Active Disturbance Rejection control Method Based on Particle Swarm Optimization 6

Quadrotor Attitude Control Under Active Disturbance Rejectio...

引用

6th international conference on Electronic engineering and Informatics, EEI 2024

作者： Yang, Guanghai Wang, Shenquan Jiang, Yulian Xue, Dongyan Changchun University of Technology School of Electrical and Electronic Engineering Changchun China Tonghua Agricultural Mechanization Technology Popularization Center Tonghua China

ISBN: (纸本)9798350353594

For solving parameter uncertainties and external interference sensitivity of quadrotor aircraft, quadrotor attitude control under an active disturbance rejection control (ADRC) scheme based on improved particle swarm optimization (PSO) algorithm is proposed. Compared with cascade PID control method, ADRC strategy adopts the concept of adaptive disturbance rejection control, it means that the disturbance model is integrated into the system model, and can directly evaluate and compensate the disturbance. Simulation results show that the auto-disturbance rejection controller designed in this paper can not only estimate and compensate the internal and external interferences, but also has strong robustness to the parameters of uncertain quadrotor aircraft. © 2024 IEEE.

关键词： Disturbance rejection

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Construction of Wind Farm Load Combination Forecasting Model Based on GBDT, LightGBM and RF 6

Construction of Wind Farm Load Combination Forecasting Model...

引用

6th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2024

作者： Xian, Qinyuan Feng, Shengjie Yang, Yajin Liu, Juan School of Aerospace Engineering Xiamen University Xiamen China School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing China School of Mechanical and Electrical Engineering China University of Mining and Technology-Beijing Beijing China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen University Xiamen China

ISBN: (纸本)9798350374315

To enhance the accuracy and effectiveness of wind farm load forecasting results, this study investigates the development of a machine learning-based wind farm load combination forecasting model. Firstly, three types of machine learning regression prediction models, namely Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF), are established. Secondly, particle swarm optimization (PSO) is employed to optimize the weighted coefficients of the combination prediction model. Finally, a GBDT-LightGBM-RF combination prediction model is constructed. the empirical analysis demonstrates that the mean square error (MSE) value of the combination forecasting model is 0.216, which is lower than that of individual forecasting models. the machine learning-based combination forecasting model significantly enhances wind power generation forecast accuracy and holds valuable implications for wind power generation planning in diverse regions. © 2024 IEEE.

关键词： Wind forecasting

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Generation and electrical Energy Demand of Hungary and Romania 6

Generation and Electrical Energy Demand of Hungary and Roman...

引用

6th IEEE international conference and Workshop Obuda on electrical and Power engineering, CANDO-EPE 2023

作者： Puiu, Petru Gabriel Istok, Robert Vasile Alecsandri University of Bacau Energetics and Computer Science Bacau Romania Óbuda University Institute of Automation and Energy Systems Budapest Hungary

ISBN: (纸本)9798350328752

this paper present the evolution of electrical energy demand in world in last years and which countries are the most biggest electrical energy consumers. the continuous increasing of energy demand is followed by the increasing of energy generation. If in case of China for example this increasing of energy generation is done with increasing of number coil based power plants, in Europe this increasing of electrical energy demand is covered with increasing of number of renewable sources. this trend is follow by Hungary and Romania too. In case of Europe 40% of electrical energy are coming from renewable sources. © 2023 IEEE.

关键词： Wind power

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Design of control system for power plant energy storage frequency regulation project 6

Design of control system for power plant energy storage freq...

引用

6th IEEE international conference on automation, Electronics and electrical engineering, AUTEEE 2023

作者： Wang, Zhongyan Jiang, Weiwei Song, Yang Li, Jia Liu, Xiwen Wang, Songhan Jilin Electric Power Research Institute Co.Ltd Changchun China Changchun Thermal Power Plant Changchun China

ISBN: (纸本)9798350305623

this paper introduces in detail the configuration scheme and control system design of energy storage auxiliary frequency regulation system in a thermal power plant. the target power plant realizes the high-efficiency application of AGC frequency regulation through retrofitting. In this paper, the AGC control strategy and the abnormal strategy of energy storage system are studied. Combined with the characteristics of regional power grid, the frequency regulation control strategy is optimized, and the AGC frequency regulation performance and depth of the target unit are significantly improved, which improves the reliability and safety of the unit operation and improves the economic benefits of the power plant. © 2023 IEEE.

关键词： abnormality AGC frequency regulation auxiliary frequency modulation control design energy storage strategy

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Optimizing Wind Speed Estimation with Least Squares Generative Adversarial Networks: A Case Study of Pakistan 6

Optimizing Wind Speed Estimation with Least Squares Generati...

引用

6th international conference on Robotics and automation in Industry, ICRAI 2024

作者： Ashfaq, Iqra Zahid, Hasan Naveed, Fajr Abid, Aaisha Uddin, Zaki NUST CEME Dept. of Electrical Engineering Islamabad Pakistan GIKI Dept. of Electrical Engineering Swabi Pakistan Fast NUCES Dept. of Computer Science Islamabad Pakistan NUST CEME Dept. of Mechatronics Engineering Islamabad Pakistan

ISBN: (纸本)9798350355703

Wind energy has emerged as a key player in sustainable power generation. Accurate prediction of wind speed is critical for optimizing wind farm operations, energy output forecasting, and reducing dependency on traditional power sources. In this study, we propose a Least-Squares Generative Adversarial Network (LSGAN) for wind speed prediction in a specific region of Pakistan, utilizing data from Tandoghulamali, which includes features like wind speeds at various altitudes and wind direction. the model is designed to predict wind speed at 80 meters, a crucial target variable for wind turbine operations. the LSGAN model effectively leverages adversarial training, achieving high accuracy with a Mean Absolute Error (MAE) of 1.54 and a Root Mean Squared Error (RMSE) of 1.77. through a detailed comparison of actual versus predicted values, the model demonstrates its ability to generalize well across unseen data, with stable performance during the adversarial learning process. this approach opens up new possibilities for applying advanced machine learning techniques in renewable energy forecasting, particularly in regions with sparse historical data. © 2024 IEEE.

关键词： Wind forecasting

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Method for Improving the Benefits of Electricity Substitution Technology Based on Fuzzy Comprehensive Evaluation 6

Method for Improving the Benefits of Electricity Substitutio...

引用

6th international conference on Information science, electrical, and automation engineering, ISEAE 2024

作者： Li, Hui Gao, Jiajie Pan, Jiajun Hong, Wei Yan, Daxin Lai, Siying Shanwei Power Supply Bureau Guangdong Power Grid Co. Ltd. Shanwei China

ISBN: (纸本)9781510682924

To achieve a more precise assessment of the comprehensive advantages of electric energy substitution technology, the article begins by conducting a thorough analysis of the various factors that influence it, ranging from a macro-level perspective to a micro-level perspective. It then proceeds to comprehensively summarize and analyze the interactions among these influencing factors. Subsequently, the article identifies the key indicators that play a decisive role in evaluating the benefits of electric energy substitution and develops a three-level evaluation network architecture model. this model combines both subjective and objective weights and employs the cloud model and entropy weight method to assign weights to the three-level indicators. this approach effectively addresses the issue of traditional assignment methods disregarding the subjective aspect. Finally, the article employs the fuzzy comprehensive evaluation method to assess the environmental benefits of electric energy substitution technology. this methodology can serve as a valuable reference for devising well-founded plans for electric energy substitution. © 2024 SPIE.

关键词： Fuzzy logic Clouds Atmospheric modeling Matrices Pollution control Carbon Energy efficiency Power grids Reliability Statistical analysis

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Fault prediction of electric vehicle charging stations based on cooperative game strategy and DBO-BiLSTM 6

Fault prediction of electric vehicle charging stations based...

引用

6th IEEE Advanced Information Management, Communicates, Electronic and automation control conference, IMCEC 2024

作者： Tian, Liguo Shang, Chunhu Li, Meng Chen, Qingbin Tianjin University of Technology and Education College of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350316520

Aiming at the problem of high failure rate of electric vehicle charging pile, an electric vehicle charging pile failure prediction method based on cooperative game strategy and dung beetle optimisation algorithm-bidirectional long and short-term memory network (DBO-BiLSTM) is proposed. Firstly, the outliers are handled by parameter statistical distribution, the missing values are handled by mean padding, and the normalisation operation is performed on the processed data;secondly, multiple single-assignment methods are selected to calculate the feature weights, the combined weights are calculated by the cooperative game strategy, and the parameter feature matrix is enlarged;and then, the DBO-BiLSTM model is constructed, and under the simulation experiments, the accuracy rate of the training set and test set, the F1 coefficients are 0.89, 0.89, 0.90 and 0.89, ***, relevant comparison experiments are constructed, and the results show that the proposed model has better performance, which verifies the effectiveness and reasonableness of the proposed model. © 2024 IEEE.

关键词： Brain

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Pulse Power Stabilizing Technology based on Combined control of Hybrid Energy Storage Systems and Generator 6

Pulse Power Stabilizing Technology based on Combined Control...

引用

6th IEEE international electrical and Energy conference, CIEEC 2023

作者： Wang, Zhengkai Zhang, Xinran Wu, Jing School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9798350346671

With the emergence of high-power density generators and the improvement of battery performance, more electric aircraft (MEA) are becoming the development direction in the aviation military field. At the actual tactical level, directed energy weapons effectively improve the technical and tactical performance of the equipment. However, the pulsed power electronic loads place higher demands on the stability of independent electric power distribution systems (EPDSs). this paper mainly focuses on the voltage stability of the 270 V high-voltage DC power system and proposes a joint droop control-based hybrid energy storage system and brushless DC motor smoothing technique, which achieves a better smoothing effect under high peak-to-average ratio pulsed power loads. the simulation results based on the PLECS simulation model validate the effectiveness of the proposed combined control approach in enhancing the stability of the aircraft's EPDS containing multiple loads. © 2023 IEEE.

关键词： Energy storage

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A Machine Learning Framework for Skin Cancer Detection using Transfer Learning 6

A Machine Learning Framework for Skin Cancer Detection using...

引用

6th IEEE international conference on Image Processing, Applications and Systems, IPAS 2025

作者： Augustine, Mary Linda Panakal Spanogianopoulos, Sotirios Sharif, Mhd Saeed University of East London School of Architecture Computing and Engineering Department of Computer Science and Digital Technologies London United Kingdom University of Portsmouth School of Electrical and Mechanical Engineering Portsmouth United Kingdom

ISBN: (纸本)9798331506520

this paper uses deep learning algorithms including InceptionV2, InceptionV3, DenseNet, MobileNet, and VGG19 to improve skin cancer detection. this research aims to improve skin cancer diagnosis. this work aims to determine the most effective evolutionary metrics-based technique to recognizing skin cancer, which is comparable to other diseases. Ultimately, our paper aims to create a realistic skin cancer detection system that uses the best deep learning algorithm. this discovery might improve medical diagnostics, leading to earlier diagnosis and improved healthcare outcomes. © 2025 IEEE.

关键词： Adversarial machine learning

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Optimization of Microbial Fuel Cells: Enhancing electrical Output through Gradient-Based Optimization 6

Optimization of Microbial Fuel Cells: Enhancing Electrical O...

引用

6th international conference on Robotics and automation in Industry, ICRAI 2024

作者： Mehmood, Hassan Zafar, Tayyab Kamal, Khurram Aun Rizvi, Syed Muhammad Ratlamwala, Tahir National University of Sciences and Technology Department of Mechatronics Engineering Islamabad Pakistan Department of Engineering Science Islamabad Pakistan

ISBN: (纸本)9798350355703

Microbial Fuel Cells (MFCs) are environment-friendly devices to generate energy through microbial metabolism of the chemical energy of organic compounds. Few of the critical challenges of implementing MFCs are their low power density, high internal resistance, and poor electron transport. these factors are major drawbacks to the MFCs efficiency and ability to scale up MFCs. the proposed work aims to enhance the MFC performance by optimizing the proportions of key operational parameters to overcome the implementation challenges. these parameters include Substrate Concentration (S), Anodophilic Biomass (xa), Methanogenic Biomass (x/m), and Oxidized Mediator (M/ox). the parameters are optimized using a Gradient Based Optimization (GBO). During the optimization process, it was imperative to establish a sound mathematical model that predicted MFC's biological and physical behavior. With the implementation of the GBO algorithm, the output current is enhanced by 8. 89 percent. the results shows that promising future of the proposed method. © 2024 IEEE.

关键词： Anodophilic Biomass Bioelectrochemical Systems Gradient-Based Optimization Methanogenic Biomass Microbial Fuel Cells Oxidized Mediator Substrate Concentration Sustainable Energy

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