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Efficient Hybrid Multi-Population Genetic Algorithm for Multi-UAV Task Assignment in Consumer Electronics Applications

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IEEE Transactions on Consumer Electronics 2025年

作者： Bai, Xiaoshan Jiang, Haoyu Li, Chao Ullah, Inam Dabel, Maryam M. Al Bashir, Ali Kashif Wu, Zongze Sam, Shuzhi Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen University Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China Tashkent State University of Economics Department of Artificial Intelligence Tashkent100066 Uzbekistan University of Hafr Al Batin Department of Computer Science and Engineering College of Computer Science and Engineering Saudi Arabia Manchester Metropolitan University Manchester United Kingdom Shenzhen518060 China National University of Singapore Department of Electrical and Computer Engineering Singapore117576 Singapore

In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp

关键词： Genetic algorithms

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On modal observers for beyond rigid body H∞ control in high-precision mechatronics*

On modal observers for beyond rigid body H∞ control in high...

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IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Hungary

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

The ever increasing need for performance results in increasingly rigorous demands on throughput and positioning accuracy of high-precision motion systems, which often suffer from position dependent effects that originate from relative actuation and sensing of the moving-body. Due to the highly stiff mechanical design, such systems are typically controlled using rigid body control design approaches. Nonetheless, the presence of position dependent flexible dynamics severely limits attainable position tracking performance. This paper presents two extensions of the conventional rigid body control framework towards active control of position dependent flexible dynamics. Additionally, a novel control design approach is presented, which allows for shaping of the full closed-loop system by means of structured H ∞ co-design. The effectiveness of the approach is validated through simulation using a high-fidelity model of a state-of-the-art moving-magnet planar actuator.

关键词： Linear systems Mechatronics Costs control design Tracking Dynamics Observers

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LPV sequential loop closing for high-precision motion systems

arXiv

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arXiv 2022年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary

Increasingly stringent throughput requirements in the industry necessitate the need for lightweight design of high-precision motion systems to allow for high accelerations, while still achieving accurate positioning of the moving-body. The presence of position dependent dynamics in such motion systems severely limits achievable position tracking performance using conventional sequential loop closing (SLC) control design strategies. This paper presents a novel extension of the conventional SLC design framework towards linear-parameter-varying systems, which allows to circumvent limitations that are introduced by position dependent effects in high-precision motion systems. Advantages of the proposed control design approach are demonstrated in simulation using a high-fidelity model of a moving-magnet planar actuator system, which exhibits position dependency in both actuation and *** Codes 93-06 © 2022, CC BY.

关键词： Linear systems

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Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexagonal Boron Nitride for Integrated Quantum Photonics

Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexa...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Roberts, Henry C. Waseem, Aadil Wicker, Scott A. Abudayyeh, Hamza Kim, Dong Seob Liu, Zhida Randolph, Steven Li, Xiaoqin Li, Xiuling Department of Electrical and Computer Engineering Microelectronics Research Center The University of Texas at Austin 10100 Harry Ransom Trail AustinTX78758 United States Department of Physics Center for Complex Quantum Systems Center for Dynamics Control of Materials Texas Materials Institute The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

We report a new approach to generate waveguide-coupled emission from deterministically implanted boron vacancy spin defects in hBN using single-crystal AlN-on-sapphire ring resonators. This facilitates the eventual development of hBN-based integrated quantum technologies. © Optica Publishing Group 2024

关键词： Single crystals

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Predictor-Based Constrained Fixed-Time Sliding Mode control of Multi-Uav Formation Flight

SSRN

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SSRN 2024年

作者： Khodaverdian, Maria Hajshirmohamadi, Shahram Hakobyan, Aleksandr Ijaz, Salman Center for Scientific Innovation and Education Aerial Robotics Laboratory of National Polytechnic University of Armenia Yerevan Armenia Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Key Laboratory of More Electric Aircraft and Control System Lab University of Nottingham Ningbo China

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicles formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational ***, a constrained performance index is constructed based on the prediction of the fixed-time sliding surface, the reaching law, and the control input. Secondly, optimal control input is calculated by solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop system stability in the presence of external disturbances and ***, the comparative evaluation with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, a test is conducted to demonstrate the algorithm's potential for hardware implementation by employing Hardware-in-the-Loop (HIL) test. © 2024, The Authors. All rights reserved.

关键词： Sliding mode control

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Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexagonal Boron Nitride for Integrated Quantum Photonics

Aluminum Nitride Ring Resonator-Coupled Spin Defects in Hexa...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Roberts, Henry C. Waseem, Aadil Wicker, Scott A. Abudayyeh, Hamza Kim, Dong Seob Liu, Zhida Randolph, Steven Li, Xiaoqin Li, Xiuling Department of Electrical and Computer Engineering Microelectronics Research Center The University of Texas at Austin 10100 Harry Ransom Trail AustinTX78758 United States Department of Physics Center for Complex Quantum Systems Center for Dynamics and Control of Materials Texas Materials Institute The University of Texas at Austin 2515 Speedway AustinTX78712 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

ISBN: (纸本)9781957171395

关键词： Aluminum nitride

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On modal observers for beyond rigid body H∞ control in high-precision mechatronics

arXiv

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arXiv 2022年

The ever increasing need for performance results in increasingly rigorous demands on throughput and positioning accuracy of high-precision motion systems, which often suffer from position dependent effects that originate from relative actuation and sensing of the moving-body. Due to the highly stiff mechanical design, such systems are typically controlled using rigid body control design approaches. Nonetheless, the presence of position dependent flexible dynamics severely limits attainable position tracking performance. This paper presents two extensions of the conventional rigid body control framework towards active control of position dependent flexible dynamics. Additionally, a novel control design approach is presented, which allows for shaping of the full closed-loop system by means of structured H∞ co-design. The effectiveness of the approach is validated through simulation using a high-fidelity model of a state-of-the-art moving-magnet planar *** Codes 37M15 © 2022, CC BY.

关键词： Closed loop systems

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Multi-microgrid Energy Management systems: Architecture, Communication, and Scheduling Strategies

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Journal of Modern Power systems and Clean Energy 2021年第3期9卷 463-476页

作者： Bin Zhou Jianting Zou Chi Yung Chung Huaizhi Wang Nian Liu Nikolai Voropai Daosen Xu the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China the Department of Electrical and Computer Engineering University of SaskatchewanSaskatoonSK S7N5A9Canada the College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China the Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences Irkutsk 664033Russia

The increasing penetration of various distributed and renewable energy resources at the consumption premises,along with the advanced metering,control and communication technologies,promotes a transition on the structure of traditional distribution systems towards cyber-physical multi-microgrids(MMGs).The networked MMG system is an interconnected cluster of distributed generators,energy storage as well as controllable loads in a distribution *** its operation complexity can be decomposed to decrease the burdens of communi-cation and control with a decentralized ***,the multi-microgrid energy management system(MIVIGEIV1S)plays a significant role in improving energy efficiency,power quality and reliability of distribution systems,especially in enhancing system resiliency during contingencies.A comprehensive overview on typical functionalities and architectures of MMGEMS is ***,the emerging communication technologies for information monitoring and interaction among MMG clusters are ***,various energy scheduling and control strategies of MMGs for interactive energy trading,multi-energy management,and resilient operations are thoroughly analyzed and ***,some challenges with great importance in the future research are presented.

关键词： Energy management system(EMS) microgrid communication renewable energy multi-energy system

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QUADFormer: Learning-based Detection of Cyber Attacks in Quadrotor UAVs

arXiv

引用

arXiv 2024年

作者： Wang, Pengyu Yang, Zhaohua Yang, Nachuan Wang, Zikai Li, Jialu Zhang, Fan Wang, Chaoqun Wang, Jiankun Meng, Max Q.-H. Shi, Ling Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The School of Control Science and Engineering Shandong University Shandong China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong Department of Electrical and Computer Engineering The University of Alberta Canada

Safety-critical intelligent cyber-physical systems, such as quadrotor unmanned aerial vehicles (UAVs), are vulnerable to different types of cyber attacks, and the absence of timely and accurate attack detection can lead to severe consequences. When UAVs are engaged in large outdoor maneuvering flights, their system constitutes highly nonlinear dynamics that include non-Gaussian noises. Therefore, the commonly employed traditional statistics-based and emerging learning-based attack detection methods do not yield satisfactory results. In response to the above challenges, we propose QUADFormer, a novel Quadrotor UAV Attack Detection framework with transFormer-based architecture. This framework includes a residue generator designed to generate a residue sequence sensitive to anomalies. Subsequently, this sequence is fed into a transformer structure with disparity in correlation to specifically learn its statistical characteristics for the purpose of classification and attack detection. Finally, we design an alert module to ensure the safe execution of tasks by UAVs under attack conditions. We conduct extensive simulations and real-world experiments, and the results show that our method has achieved superior detection performance compared with many state-of-the-art methods. (Video1) Copyright © 2024, The Authors. All rights reserved.

关键词： Antennas

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

引用

Annual Conference of Industrial Electronics Society

作者： Haibo Cheng Yunpeng He Peng Zeng Shichao Li Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction.

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