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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Yongfeng Zhang, Yuze Ma, Lijia Ji, Junkai Liu, Dugang Leung, Victor C. M. Li, Jianqiang Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen518123 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China The University of British Columbia Department of Electrical and Computer Engineering VancouverV6T 1Z4 Canada

ISBN: (纸本)9798350308365

Cooperative co-evolution (CC) is a promising direction in solving large-scale multiobjective optimization problems (LMOPs). However, most existing methods of grouping decision variables face some difficulties when searching in the huge search space. Specifically, the methods of grouping decision variables can be classified into two types, i.e., high-consumption grouping methods and non-consumption grouping methods. On the one hand, the former ones divide the decision variables into different groups based on the correlation analysis between variables, which consume much evaluation. This way may lead to premature convergence within limited computational resources. On the other hand, the later ones allocate the decision variables into sub-groups based on some metrics, e.g., order and size, which consume no evaluation while may cause the search fall into local optima. To alleviate the above issues, this paper proposes a CC-based algorithm with a variable-importance grouping (VIG) method, called VICCA. Firstly, the decision variables are classified into several subgroups according to their importance quantified by a meta-gene construction method. Secondly, a CC strategy is designed to simultaneously optimize all subgroups of decision variables formed by VIG using the differential evolution operator, which aims to accelerate the convergence speed. Thirdly, a global evolutionary strategy is proposed to optimize original decision variable space by the competitive swarm optimizer, aiming to maintain the diversity. Finally, the experiments demonstrate that our proposed VICCA has the significant advantage in solving LMOPs when compared with state-of-the-art evolutionary algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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Optical-Based Relative Electric Field Measurement in Dielectric Microwave Resonators 5

Optical-Based Relative Electric Field Measurement in Dielect...

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5th IEEE research and Applications of Photonics in Defense Conference, RAPID 2022

作者： Dev, Sukrith Anthony, Nathan Trendafilov, Simeon Allen, Monica Allen, Jeffery Munitions Directorate Eglin Air Force Base Air Force Research Laboratory United States University of Central Florida Department of Electrical and Computer Engineering Orlando United States

ISBN: (数字)9781665402231

ISBN: (纸本)9781665402231

Here we present the experimental relative electric field magnitude mapping of a high permittivity cylindrical dielectric microwave resonator mode using an external superstrate optically induced conductance (OIC) technique. The fundamental TE01δ mode is mapped and compared to finite element method simulated fields with excellent agreement. © 2022 IEEE.

关键词： Electric fields

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Self-polarized RGB device realized by semipolar micro-LEDs and perovskite-in-polymer films for backlight applications

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Opto-Electronic Advances 2024年第3期7卷 35-49页

作者： Tingwei Lu Yue Lin Tianqi Zhang Yue Huang Xiaotong Fan Shouqiang Lai Yijun Lu Hao-Chung Kuo Zhong Chen Tingzhu Wu Rong Zhang School of Electronic Science and Engineering Fujian Engineering Research Center for Solid-State LightingXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Department of Photonics and Graduate Institute of Electro-Optical Engineering College of Electrical and Computer EngineeringYang Ming Chiao Tung UniversityHsinchu 30010China Semiconductor Research Center Hon Hai Research InstituteTaipei 11492China.

In backlighting systems for liquid crystal displays,conventional red,green,and blue(RGB)light sources that lack polarization properties can result in a significant optical loss of up to 50%when passing through a *** address this inefficiency and optimize energy utilization,this study presents a high-performance device designed for RGB polarized *** device employs an array of semipolar blueμLEDs with inherent polarization capabilities,coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid *** CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission,while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions,due to their high dielectric *** resulting device achieved RGB polarization degrees of 0.26,0.48,and 0.38,respectively,and exhibited a broad color gamut,reaching 137.2%of the NTSC standard and 102.5%of the Rec.2020 *** compared to a device utilizing c-plane LEDs for excitation,the current approach increased the intensity of light transmitted through the polarizer by 73.6%.This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

关键词： halide perovskite light-emitting-diodes polarized emission nanocrystals stability

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Stochastic Characterization-Based Performance Analysis of an Emulated Communication Network for Cyber- Physical Shipboard Power Systems

Stochastic Characterization-Based Performance Analysis of an...

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IEEE Electric Ship Technologies Symposium, ESTS

作者： Mahmoud S. Abdelrahman Tung-Lam Nguyen Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

Emerging advanced and innovative Information and Communication Technologies (ICT), automation strategies, and associated algorithms in the traditional power system have transformed it into a Cyber-Physical Power System (CPPS). Energy management and control are crucial in the Shipboard Power System operation. For instance, to meet the ship's energy and other ancillary demands, especially the mission-critical loads that require practical and secure network communication. Therefore, a comprehensive modeling and testing and validation approach was developed in this paper. This enables flexible system-level aspect evaluation through numerous experiments, including virtual, real, and mixed lab settings. This paper presents a scalable and flexible three-layer cyber-physical co-simulation platform implemented in the FIU smart grid testbed. This includes real-time power system simulation using OPAL-RT, ns3 for communication network emulation, and MATLAB/SIMULINK for implementing various applications. To demonstrate the platform's effective operation, energy management with a central controller for SPS was configured and implemented to test the communication network performance by creating tools to characterize the network latency for this application.

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Robust Control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Deep Unfolded Tensor Robust PCA With Self-Supervised Learning

Deep Unfolded Tensor Robust PCA With Self-Supervised Learnin...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Harry Dong Megna Shah Sean Donegan Yuejie Chi Department of Electrical and Computer Engineering Carnegie Mellon University Materials and Manufacturing Directorate Air Force Research Laboratory

Tensor robust principal component analysis (RPCA), which seeks to separate a low-rank tensor from its sparse corruptions, has been crucial in data science and machine learning where tensor structures are becoming more prevalent. While powerful, existing tensor RPCA algorithms can be difficult to use in practice, as their performance can be sensitive to the choice of additional hyperparameters, which are not straightforward to tune. In this paper, we describe a fast and simple self-supervised model for tensor RPCA using deep unfolding by only learning four hyperparameters. Despite its simplicity, our model expunges the need for ground truth labels while maintaining competitive or even greater performance compared to supervised deep unfolding. Furthermore, our model is capable of operating in extreme data-starved scenarios. We demonstrate these claims on a mix of synthetic data and real-world tasks, comparing performance against previously studied supervised deep unfolding methods and Bayesian optimization baselines.

关键词： Tensors Signal processing algorithms Self-supervised learning Signal processing Transformers Task analysis Speech processing

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ANN-Based Secure Control of Islanded Microgrid Under False Data Injection Cyber-Attack

ANN-Based Secure Control of Islanded Microgrid Under False D...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ibtissam Kharchouf Mahmoud S. Abdelrahman Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

AC microgrids may be a target of cyber-attacks such as False Data Injection attack (FDIA) or Denial of Service attacks due to the use of communication technologies. These types of attacks target the communication infrastructure or the control system itself. For instance, FDIAs aim to inject false data into AC microgrids to disrupt the control system. Techniques that detect and mitigate the effect of such attacks are needed. This paper presents an AC microgrid that is structured by parallel inverters and controlled by distributed consensus control strategies to control the frequency and voltage magnitude through active and reactive power. We will investigate the FDIAs effect on the AC microgrid operation. A viable solution to address the FDIA attacks in AC microgrids is developed using an ANN-based reference tracking application to detect and mitigate the attack. The simulation results proved that the proposed strategy could detect and mitigate FDIA attacks especially if the ANN is well trained.

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Directional Modulation for Multi-Node Interaction from an Artificially Intelligent Power Amplifier Array: Simultaneous Radar and Communication while Optimizing Circuit Performance

Directional Modulation for Multi-Node Interaction from an Ar...

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IEEE National Conference on Radar

作者： Samuel Haug Adam Goad Austin Egbert Charles Baylis Anthony Martone Benjamin Kirk Robert J. Marks II Department of Electrical and Computer Engineering Baylor University Waco TX DEVCOM Army Research Laboratory Adelphi MD

Spectral efficiency and security in wireless applications can be enhanced through directional transmission of multiple signals from a single array aperture. Directional modulation allows the array to transmit multiple, directionally distinct signals out of the same aperture at the same time and frequency. This is accomplished through calculated antenna current excitations to ensure desired directional transmissions. A critical issue in this process involves the power amplifiers in each array element. Due to mutual coupling differences between array elements and the variations in power amplifier nonlinearities, signals leaving the power amplifiers may be distorted and no longer contain the desired information. This can result in bit errors in communication. To correct this issue, real-time impedance tuning and signal equalization are applied to reduce the distortion of the directionally transmitted messages. Signal equalization is corrective feedback technique similar to digital predistortion (DPD). Experimental simulation results are presented using directional modulation in an array of power amplifiers with reconfigurable load impedance tuners. The signal equalization technique applies corrective feedback to adjust the amplifier input signals, compensating for the undesired distortion such that the desired currents will be input to the antennas. Because the impedance tuning and signal equalization techniques may have conflicting effects on the overall distortion, impedance tuning is applied initially, and signal equalization is applied after the impedance tuning operation is complete.

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Frequency Stability Enhancement in Low-Inertia Power System Using an Optimal Control Scheme

Frequency Stability Enhancement in Low-Inertia Power System ...

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International Conference on Environment and electrical engineering (EEEIC)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

Power system dynamics have significantly changed with the global integration of renewable energy sources (RESs). Traditionally, the stored kinetic energy is used for compensating the generation mismatch using the rotating mass of the Synchronous Generators (SGs). With the increase in RESs penetration, SGs are being replaced by inverter-based RESs generation systems which are decoupled from the power systems through power converters. Therefore, the total inertia of the system has decreased, and the system's stability is significantly impacted as the value of the rate of change of frequency (ROCOF) and frequency deviations will be increased. To overcome these challenges, inertia emulation from various energy storage systems (ESS) is used to act as a virtual source of inertia power. This work presents an isolated microgrid (MG) that includes conventional power generation sources and RESs, and an optimal virtual inertia (VI) control loop is proposed for frequency stability enhancement. Supercapacitors (SC) bank with a PID controller presents the VI control loop and acts as a supplementary source for inertia power to support the frequency stability of the system. A genetic algorithm (GA) is used as an optimization technique to get the optimal values of the PID controller gains. The performance of the islanded MG with the proposed optimal control scheme is examined under different operating conditions with varying levels of RESs penetration and system parameters uncertainties. The proposed technique showed its effectiveness and robustness over the system's operation without VI control for keeping the system stable under different operating conditions.

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Channel Knowledge Map for Cellular-Connected UAV via Binary Bayesian Filtering

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IEEE Transactions on Communications 2025年

作者： Yang, Yuhang Xu, Xiaoli Zeng, Yong Sun, Haijian Hu, Rose Qingyang Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China University of Georgia School of Electrical and Computer Engineering AthensGA United States Utah State University Department of Electrical and Computer Engineering LoganUT United States

Channel knowledge map (CKM) is a promising technology to enable environment-aware wireless communications and sensing. Link state map (LSM) is one particular type of CKM that aims to learn the location-specific line-of-sight (LoS) link probability between the transmitter and the receiver at all possible locations, which provides the prior information to enhance the communication quality of dynamic networks. This paper investigates the LSM construction for cellular-connected unmanned aerial vehicles (UAVs) by utilizing both the expert empirical mathematical model and the measurement data. Specifically, we first model the LSM as a binary spatial random field and its initial distribution is obtained by the empirical model. Then we propose an effective binary Bayesian filter to sequentially update the LSM by using the channel measurement. To efficiently update the LSM, we establish the spatial correlation models of LoS probability on the location pairs in both the distance and angular domains, which are adopted in the Bayesian filter for updating the probabilities at locations without measurements. Simulation results demonstrate the effectiveness of the proposed algorithm for LSM construction, which significantly outperforms the benchmark scheme, especially when the measurements are sparse. © 1972-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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