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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Koti, Hossein Nejadi Valipoor, Zahra Demerdash, Nabeel A. O. Rockwell Automation Inc. Motion Control Team Mequon United States Marquette University Electrical and Computer Engineering Department Milwaukee United States

ISBN: (纸本)9798350316445

Sensitivity analysis is a powerful tool that can be utilized for reducing the size of the design space at hand to explore and significantly reduce the computational burden of the optimization process. This is achieved by 'smart' design variable selection. The term 'smart' indicates fixing the un-conflicting design variables that do not require exploration to their maximum or minimum values, depending on their enhancing or degrading effect on the objective functions and allowing the conflicting design variables to be explored within their allowable dynamic range. Intelligent optimization is a critical part of induction motor design process. In this paper, computationally efficient sensitivity analysis is performed to effectively reduce the number of the design variables that will be actively explored in the optimization process of the induction motors. This goal is achieved through the VBR-based TS-FEA together with Design of Experiment and Response Surface Methodology. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components. © 2023 IEEE.

关键词： Core Losses Induction Motor Temperature Thermal Calibration VBR-based FEA

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Personalized Semantic Trajectory Privacy Protection in Location-Based Services: A TD3-Based Approach

Personalized Semantic Trajectory Privacy Protection in Locat...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Ye, Jun Dai, Minghui Min, Minghui Song, Jinling Zhang, Hongliang Han, Zhu School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China School of Electronics Peking University Beijing100871 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States

ISBN: (纸本)9798350368369

The swift advancement of Location-Based Services (LBSs) raises the danger of trajectory privacy being breached, since the location semantic tags can easily disclose users' sensitive information. Additionally, attackers can exploit temporal correlations to infer sensitive personal information. This paper formulates a personalized semantic trajectory privacy protection framework designed to protect locations with varying sensitivities on the trajectory from the attacker with temporal correlation information. We model the trajectory privacy protection problem as a Markov Decision Process (MDP) and introduce the Reinforcement Learning (RL) technique to dynamically adjust the privacy parameters. Specifically, we leverage the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to enhance the stability and accuracy of policy evaluation, enabling efficient learning of optimal policies in continuous action spaces. Simulation results indicate that the TD3-based personalized semantic trajectory privacy protection mechanism effectively balances the Quality of Service and semantic trajectory privacy while realizing personalized trajectory privacy protection. © 2025 IEEE.

关键词： Reinforcement learning

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MulDoor: A Multi-target Backdoor Attack Against Federated Learning System

MulDoor: A Multi-target Backdoor Attack Against Federated Le...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Xuan Wu, Longfei Guan, Zhitao Du, Xiaojiang Aitsaadi, Nadjib Guizani, Mohsen North China Electric Power University School of Control and Computer Engineering China Fayetteville State University Department of Mathematics and Computer Science Fayetteville United States Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States Université Paris-Saclay Uvsq David Versailles France Machine Learning Department United Arab Emirates

ISBN: (纸本)9798350351255

In recent years, with the development of wireless communication networks, federated learning (FL) has been widely deployed in distributed scenarios as a privacy-preserving machine learning paradigm. Due to its inherent features, FL shows vulnerability to backdoor attacks. In a backdoor attack, an adversary manipulates the global model's output by compromising the model of one or multiple participants. Existing backdoor attacks are constrained to outputting a single specified target label during the inference phase, limiting the adversary's flexibility to alter the model's output when different target labels are required. In this paper, we study the multi-target attack scenario within the federated learning context, where the adversary aims to manipulate the global model to output various specified labels by inserting different types of triggers. To effectively insert multiple backdoors simultaneously without reducing the attack's effectiveness, we propose MulDoor, a novel multi-target backdoor attack scheme. MulDoor incorporates the concept of supervised contrastive learning to learn the discrepancies among different types of triggers and mitigate interference between them. The experimental results demonstrate that MulDoor achieves better attack effectiveness compared to existing backdoor attacks in a multi-target backdoor attack setting. © 2024 IEEE.

关键词： Contrastive Learning

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Personalized Privacy Protection Incentive Mechanism for Mobile Crowdsourcing Based on Homomorphic Encryption and Edge Computing

Personalized Privacy Protection Incentive Mechanism for Mobi...

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IEEE International Conference on Web Services (ICWS)

作者： Yingxin Li Weilong Wang Yingjie Wang Tong Xiangrong Peiyong Duan Zhipeng Cai Department of Computer and Control Engineering Yantai University Department of Computer Science and Engineering Southeast University Department of Electrical and Control Qilu University of Technology Department of Computer Science Georgia State University

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

With the rapid development of crowd sensing computing, Mobile crowdsourcing (MCS) has become an indispensable part of today’s society. While MCS brings convenience to people, it also exposes them to the risk of privacy leakage. In addition, the demand for data is increasing, and the personalized privacy requirements of crowd workers may affect the service quality. In order to address these problems, this paper proposes a personalized privacy protection incentive mechanism (PPPIM) for MCS based on homomorphic encryption and edge computing. Firstly, this paper designs a personalized privacy metric, using social attributes and private attributes of crowd workers to calculate the privacy level required by crowd workers. Then, based on homomorphic encryption and edge computing, a personalized residual federated security learning scheme (PRFSL) is proposed to ensure the security, timeliness, integrity of task data and the privacy of crowd workers’ needs to improve encryption efficiency. Finally, based on the evolutionary game, a personalized privacy incentive mechanism is proposed to improve the overall service utility. Experimental comparisons based on real datasets show that the proposed scheme can not only ensure the security, timeliness, and integrity of task data more effectively. It can also effectively reduce data processing time, improve the probability of crowd workers actively completing tasks and the overall service quality utility.

关键词： Crowdsourcing Measurement Privacy Data privacy Web services Sensors Homomorphic encryption Protection Mobile computing Edge computing

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Output Tracking control of a Nonlinear System Based on Takagi-Sugeno Fuzzy Model: Generalized Partial Eigenstructure Assignment Approach

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IEEE Access 2024年 12卷 18520-18535页

作者： Soltanian, Farzad Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2M9 Canada Shiraz University of Technology Electrical Engineering Faculty Shiraz71557-13876 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2-performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2-performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems. © 2013 IEEE.

关键词： Transient analysis

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Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation Relieving Design for Doubly Salient Reluctance Machine Position Sensorless Drive Electric Propulsion Applications 6

Tangentially-Magnetized-Slot-PM-Assisted Magnet Saturation R...

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6th International Conference on electrical engineering and control Technologies, CEECT 2024

作者： Wang, Weiyu Zhang, Xiaodong Niu, Shuangxia Zhao, Xing Pan, Jianfei Fu, Weinong Great Bay University School of Engineering Dongguan China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong University of York Department of Electronic Engineering York United Kingdom Shenzhen University College of Mechatronics and Control Engineering Shenzhen China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen China

ISBN: (纸本)9798331528096

For doubly salient reluctance machines, the magnetic saturation effect easily occurs, thereby the saturated inductance with complex analytical expression brings difficulties to the inductance modeling procedure during position sensorless control. To tackle this issue, a direct solution from electrical machine design is introduced to regulate magnetic flux distribution. The key is to insert tangentially-magnetized-slot-permanent-magnet into stator slots, thus relieving the magnetic saturation in the stator teeth. Consequently, unsaturated inductance characteristics can be acquired through the magnetic saturation relieving effect, thereby the inductance modeling effort can be significantly decreased, and such design is friendly for doubly salient reluctance machine position sensorless drive application. © 2024 IEEE.

关键词： Stators

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Dubins Vehicle Intercept of a Brownian Target on a Sphere 63

Dubins Vehicle Intercept of a Brownian Target on a Sphere

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Milutinovic, Dejan Casbeer, David W. University of California Department of Electrical and Computer Engineering Santa CruzCA United States Air Force Research Laboratory Control Science Center Wright-Patterson AFBOH United States

ISBN: (纸本)9798350316339

This paper focuses on a navigation of a Dubins vehicle (DV) to intercept a moving target on a sphere. The uncertainty in the target motion is described by a Brownian motion model. An Itô-type stochastic differential equation for the relative motion between DV and the Brownian moving target is derived. This stochastic differential equation is used to formulate an intercept controller as a minimum time optimal controller. The properties of the controller are incorporated into the numerical computations of the controller, which by its construction can intercept a Brownian target. Our numerical simulation results show that the computed controller can intercept both stationary and moving targets on the sphere. © 2024 IEEE.

关键词： Stochastic systems

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Equilibrium-Independent control of Continuous-Time Nonlinear Systems Via the LPV Framework

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IEEE Transactions on Automatic control 2025年

作者： Koelewijn, Patrick J. W. Weiland, Siep Toth, Roland Eindhoven University of Technology Control Systems Group Department of Electrical Engineering Eindhoven Netherlands Institute for Computer Science and Control Systems and Control Laboratory Budapest Hungary

In this paper, we consider the analysis and control of continuous-time nonlinear systems to ensure universal shifted stability and performance, i.e., stability and performance w.r.t. each forced equilibrium point of the system. This "equilibrium-free"concept is especially beneficial for control problems that require the tracking of setpoints and rejection of persistent disturbances, such as input loads. In this paper, we show how the velocity form, i.e., the time-differentiated dynamics of the system, plays a crucial role in characterizing these properties and how the analysis of it can be solved by the application of Linear Parameter-Varying (LPV) methods in a computationally efficient manner. Furthermore, by leveraging the properties of the velocity form and the LPV framework, a novel controller synthesis method is presented which ensures closed-loop universal shifted stability and performance. The proposed controller design is verified experimentally on a real system. Additionally, we compare the proposed method to a standard LPV control design, demonstrating the improved stability and performance guarantees of the new approach. © 1963-2012 IEEE.

关键词： control system synthesis

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis 2

Complex Permeability Determination for EE Core Based on Flex...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Jie, Huamin Zhao, Zhenyu Chang, Yongqi Wang, Changdong Jiang, Shiqi Gao, Richard Xian-Ke See, Kye Yak School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of High Performance Computing A*STAR Singapore Singapore

ISBN: (纸本)9798331509552

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz. ©2024 IEEE.

关键词： Magnetic flux

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