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Artificial neural network-based direct power control to enhance the performance of a PMSG-wind energy conversion system under real wind speed and parameter uncertainties: An experimental validation

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Energy Reports 2024年 11卷 4356-4378页

作者： Majout, Btissam Bossoufi, Badre Karim, Mohammed Skruch, Pawel Mobayen, Saleh El Mourabit, Youness El Zair Laggoun, Zakaria Laboratory of Engineering Modelling and Systems Analysis SMBA University Fez Morocco Department of Automatic Control and Robotics AGH University of Krakow Poland Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan National School of Applied Sciences Abdelmalek Essaadi University Tetouan Morocco Laboratory of Electrotechnique Constantine Mentouri Brothers Constantine 1 University Constantine Algeria

With the increasing emphasis on embedding advanced technology into system controls, the Direct Power control (DPC) approach has garnered considerable attention due to its simple and highly adaptable algorithm. This approach has been increasingly recognized in numerous applications. However, the variable frequency, harmonic distortion of the currents, and power ripples caused by Hysteresis controllers and switching tables decrease its effectiveness and robustness, affecting the system's performance. For this reason, this paper proposed a new DPC based on Artificial Neural Network (ANN) approaches. In this approach, the hysteresis comparator and the switching table are substituted with ANN controllers and then applied on both sides: machine-side converter (MSC) and grid-side converter (GSC) of a Permanent Magnet Synchronous Generator based Wind Energy Conversion System (PMSG-WECS). Moreover, to make the system more efficient in varying wind conditions, this study expands the utilization of the artificial neural networks (ANN) to encompass the maximum power point tracking (MPPT) control strategy. To demonstrate the effectiveness of the proposed approach on the system behaviors, a simulation test was carried out in the Matlab/Simulink environment, using a real wind profile of a Moroccan city (Essaouira). In comparison to the classical DPC control, the simulation results showed the superior performance of the proposed ANN-DPC control in terms of reference tracking, response time, overshoot, precision, and its capacity to reduce the rate of power ripples and total harmonic distortion (THD) in the injected currents. Furthermore, a robustness test was also included in this work to check the robustness of the proposed control against parameters variation. In conclusion, the feasibility and effectiveness of the ANN-DPC control approach were confirmed through experimental validation using the dSPACE DS1104 board. © 2024 The Authors

关键词： MATLAB

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Predictive Vehicle control at Intersections with Look-Ahead Driving Approach

Predictive Vehicle Control at Intersections with Look-Ahead ...

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SICE International Symposium on control Systems (ISCS)

作者： Atykhan Magzhan Md Delowar Hossain A. S. M. Bakibillah Md Abdus Samad Kamal Kou Yamada Graduate School of Science and Technology Gunma University Kiryu Japan Department of Systems and Control Engineering Institute of Science Tokyo Tokyo Japan

ISBN: (数字)9784907764852

ISBN: (纸本)9798331533502

This paper presents a look-ahead vehicle control scheme for efficient traffic management at signalized inter-sections. The proposed scheme predicts future driving states with a look-ahead approach as an extended adaptive cruise control (ACC) model. It maintains car-following behavior similar to human driving while predicting future states of traffic flow to minimize intersection clearing time and aggressive braking independently, similar to model predictive control (MPC) approaches. In contrast to MPC models that are computationally demanding and have limited practical applications due to real-time constraints, the proposed scheme uses a modified Intelligent Driver Model (IDM) with predictive adjustments. The efficiency of the control scheme is evaluated through simulations with multiple vehicles in intersection traffic scenarios, focusing on maintaining safe time headway within a traffic flow and ensuring efficient flows with higher intersection throughput. Comparative results indicate improvements in intersection clearance, human-like vehicle headway management, and enhanced traffic flow performance.

关键词： Adaptation models Computational modeling Heuristic algorithms Predictive models Prediction algorithms Real-time systems Safety Vehicle dynamics Predictive control Vehicles

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Methane and nitrous oxide emissions from municipal wastewater treatment plants in China:A plant-level and technology-specific study

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Environmental Science and Ecotechnology 2024年第4期20卷 123-130页

作者： Haiyan Li Liangfang You He Du Bowen Yu Lu Lu Bo Zheng Qiang Zhang Kebin He Nanqi Ren School of Civil and Environmental Engineering Harbin Institute of TechnologyShenzhen518055China Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China

Wastewater treatment is an important source of greenhouse gases(GHGs).Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants(MWWTPs)in China.A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of *** we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level ***'s methane(CH_(4))and nitrous oxide(N_(2)O)emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg,respectively,with the uncertainty range of-30%to 37%and-30%to 26%at 95%confidence *** find an emission inequality across cities,with the richest cities emitting two times more CH_(4)and N_(2)O per capita from municipal wastewater treatment than the poorest *** emitted CH_(4)and N_(2)O are dominated by Anaerobic/Anoxic/Oxic-,Sequencing Batch Reactor-,Oxidation Ditch-,and Anoxic/Oxic-based MWWTPs of less than 20 years *** the relatively young age structure of China's MWWTPs,the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation *** emission differences among our estimates,previous studies,and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors,implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.

关键词： Methane Nitrous oxide Emissions Municipal wastewater treatment plants

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RISense: 6G-Enhanced Human Activity Recognition System with RIS and Deep LDA 25

RISense: 6G-Enhanced Human Activity Recognition System with ...

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25th IEEE International Conference on Mobile Data Management, MDM 2024

作者： Rizk, Hamada Hashima, Sherief Osaka University Graduate School of Information Science and Technology Suita565-0871 Japan Tanta University Computer and Control Engineering Department Tanta31733 Egypt RIKEN-AIP Computational Learning Theory Team Fukuoka819-0395 Japan Egyptian Atomic Energy Authority Engineering Dept Cairo13759 Egypt

ISBN: (纸本)9798350374551

Human Activity Recognition (HAR) systems hold great potential in aiding disabled and elderly individuals to live independently. Various approaches have been suggested for identifying human activities, including sensors, cameras, wearables, and contactless microwave sensing. This latter method is gaining significant attention due to its ability to address privacy concerns arising from cameras and alleviate discomfort caused by wearables. However, current microwave sensing techniques have a key limitation, requiring controlled and ideal conditions to achieve accurate activity detection. In this paper, we propose RISense, a deep learning-aided system for HAR using Re-configurable Intelligent Surface (RIS). RISense introduces novel modules designed to generate a human activity representational space that ensures separability between activity classes, even in the presence of noisy and distorted Channel State Information (CSI) measurements. These representations are then fed into a Recurrent Neural Network (RNN), which learns the sequential changes in features to accurately estimate the user activity. The evaluation of RISense across two realistic settings, encompassing both non-line-of-sight and multi-floor scenarios, showcases its efficacy. Specifically, RISense achieves an activity recognition accuracy of 98.7%. This performance overcomes the accuracy of state-of-the-art systems by over 15%. These findings highlight the superior efficacy of the proposed methodologies, including integrating RIS and advanced learning techniques. © 2024 IEEE.

关键词： Channel state information

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Prediction of Therapy Response in Patients with NSCLC based on CT Images 2022

Prediction of Therapy Response in Patients with NSCLC based ...

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4th International Conference on Intelligent Medicine and Image Processing, IMIP 2022

作者： Zhang, Xianru Liu, Lixin Chen, W.E.I. Yang, Fengchang Qiao, X.U. Chen, Yen-Wei Department of Biomedical Engineering School of Control Science and Engineering Shandong University China School and Hospital of Stomatology Shandong University China Department of Radiology Shandong Cancer Hospital and Institute Cheeloo College of Medicine Shandong University China Graduate School of Information Science and Engineering Ritsumeikan University Japan

ISBN: (纸本)9781450396202

Lung cancer has the highest mortality rate, and patients with non-small cell lung cancer (NSCLC) account for 75% to 80% of these cases. Treatment response varies greatly among patients. Therefore, there is significant clinical value in predicting the therapy efficacy for patients. In this paper, we investigated the therapy efficacy prediction model based on CT images, including traditional radiomics methods and deep learning models in 2D and 3D. The model based on ResNet18 showed predictive performance and outperformed the conventional radiomics models in prediction. © 2022 ACM.

关键词： Forecasting

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Study on the Learning in Intelligent control Using Neural Networks Based on Back-Propagation and Differential Evolution 4th

Study on the Learning in Intelligent Control Using Neural Ne...

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4th EAI International Conference on robotic Sensor Networks, 2020

作者： Mu, Shenglin Shibata, Satoru Lu, Huimin Yamamoto, Tomonori Nakashima, Shota Tanaka, Kanya Graduate School of Science and Engineering Ehime University Ehime Matsuyama Japan Faculty of Engineering Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Kitakyushu-shi Japan Graduate School of Sciences and Technology for Innovation Yamaguchi University Yamaguchi Ube Japan School of Science and Technology Meiji University Kanagawa Kawasaki Japan

ISBN: (纸本)9783030704506

In order to obtain good control performance of ultrasonic motors in real applications, a study on the learning in intelligent control using neural networks (NN) based on differential evolution (DE) is reported in this chapter. To overcome the problems of characteristic variation and nonlinearity, an intelligent PID controller combined with DE type NN is studied. In the proposed method, an NN controller is designed for estimating the variation of PID gains, adjusting the control performance in PID controller to minimize the error. The learning of NN is implemented by DE in the update of the NN’s weights. By employing the proposed method, the characteristic changes and nonlinearity of USM can be compensated effectively. The effectiveness of the method is confirmed by experimental results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Three term control systems

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Lexicographic Multi-objective Order Picking Optimization for robotic Mobile Fulfillment Systems

Lexicographic Multi-objective Order Picking Optimization for...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Wang, Hanying Zhao, Ziyan Liang, Jiaqi Li, Xingyang Liu, Shixin College of Information Science and Engineering Northeastern University Shenyang110819 China Foshan Graduate School of Innovation Northeastern University Foshan China Polytechnique Montréal Département de Mathématiques et Génie Industriel MontréalQCH3T 1J4 Canada Faculty of Robot Science and Engineering Northeastern University Shenyang110819 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries The College of Information Science and Engineering Shenyang110819 China School of Control Engineering/School Northeastern University at Qinhuangdao Hebei Qinhuangdao066004 China

ISBN: (纸本)9781665410205

In light of advancements in artificial intelligence, the Internet of Things, and mechatronics, robots are increasingly integrated into e-commerce warehouses to enable smart order picking solutions and foster intelligent automation. A robot-assisted order picking process revolutionizes the traditional labor-intensive person-to-goods order picking technology, leading to a goods-to-person (G2P) smart warehouse. Within it, robots transport pods to predefined picking stations, where human pickers retrieve the requested goods from these pods to fulfill customer orders. The allocation of pods to robots and the scheduling of picking operations are key optimization issues in G2P order picking systems. Although they play a key role in improving operational efficiency, existing research has paid limited attention to their joint optimization. This study considers a lexicographic multi-objective optimization problem to shorten the order picking cycles under the premise of optimizing the picking efficiency evaluated by makespan. We build a mixed integer program for the newly proposed problem and develop a matheuristic algorithm by integrating a commodity-order model into a metaheuristic algorithm to solve it. Experimental results show that the proposed method can significantly shorten the total order picking cycles while keeping the minimum makespan. It outperforms a recent state-of-the-art algorithm. This work emphasizes the importance of joint optimization within G2P smart warehouses and reveals the high potential of the proposed method to be used in practice. © 2024 IEEE.

关键词： Integer programming

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An Optimized Ensemble Model for Prediction the Bandwidth of Metamaterial Antenna

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Computers, Materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed Ibrahim Hattan F.Abutarboush Ali Wagdy Mohamed Mohamad Fouad El-Sayed M.El-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(ML)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the Metamaterial *** base models are used namely:Multilayer Perceptron(MLP)and Support Vector Machines(SVM).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： Metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

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Study on the Applicability Considering on the Relationship between Shape and Flexibility of the Adsorption Gripper Tip 7

Study on the Applicability Considering on the Relationship b...

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7th International Conference on control and robotics engineering, ICCRE 2022

作者： Ofuchi, Akira Fujiwara, Daisuke Iizuka, Kojiro Shibaura Institute of Technology Graduate School of Systems Engineering and Science Saitama Japan Suwa University of Science Faculty of Engineering Department of Mechanical & Electrical Engineering Chino Japan Shibaura Institute of Technology Department of Machinery and Control System Saitama Japan

ISBN: (纸本)9781665468404

This study considers automatic scallop harvesting using the drone with the robot arm as the new scallop fishery. The fishery needs the dedicated gripper attaching the robot arm. This study judges the adsorption gripper as the dedicated gripper. The adsorption gripper must push itself to the object during gripping motion. If the pushing force is too large, there are some problems with the grasping. This study focuses on the flexibility of the gripper tip contacting object to solve those problems. Then, we investigate the applicability considering on the relationship between shape and flexibility of the adsorption gripper tip from the experiment. From these considerations, the dedicated gripper has been developed. © 2022 IEEE.

关键词： Adsorption

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General Kinematics and Simulation for Mobile robot Adapted Three Unconstraint Rollers

General Kinematics and Simulation for Mobile Robot Adapted T...

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Electrical, Computer and Energy Technologies (ICECET), International Conference on

作者： Kenji Kimura Kazuo Ishii Department of Control Engineering National Institute of Technology Matsue College Shimane Japan Graduate School of Life Science and engineering Kyushu Institute of Technology Fukuoka Japan

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

In recent years, efficient mobility is required for omni-directional mobile robots in the logistics industry. There are various types of rollers mounted on mobile robots. Among them, omni-directional rollers (omni roller) are considered to have excellent omni-directional mobility and easy control. Assuming a circular mechanism, kinematics has been derived assuming an arbitrary arrangement along this circumference, and several studies have evaluated roller arrangements in terms of the speed efficiency of the driving rollers. To evaluate the roller arrangement, kinematics is necessary, in which not only the contact position of the rollers but also the direction is a parameter. In this study, kinematics is derived for a mobile robot equipped with three omni-rollers, with the contact position and direction of the rollers as parameters, and the behaviors of the roller velocity is investigated for the robot's movement in all directions.

关键词： Industries Contacts Kinematics Vectors Mobile robots Logistics

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