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PV Maximum Power-point Tracking Using Modified Particle Swarm Optimization under Partial Shading Conditions

Chinese Journal of electrical engineering 2020年第4期6卷 106-121页

作者： Al-wesabi Ibrahim M.B.Shafik Min Ding Mohammad Abu Sarhan Zhijian Fang Ahmed.G.Alareqi Tariq Al’moqri Ayman.M.Al-Rassas School of Automation China University of GeoscienceWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Oil and Natural Gas Engineering China University of GeosciencesWuhan 430074China School of Mathematics and Physics China University of GeoscienceWuhan 430074China School of Petroleum Engineering China University of PetroleumEast ChinaQingdao 266580China

A novel maximum power-point tracking approach is proposed based on studies investigating the output characteristics of photovoltaic(PV)systems under partial shading *** existence of partially shaded conditions leads to the presence of several peaks on PV curves,which decrease the efficiency of conventional ***,the proposed algorithm,which is based on the modified particle-swarm optimization(MPSO)technique,increases the output power of PV systems under such abnormal conditions and has a better performance compared to other *** proposed method is examined under several scenarios for partial shading condition and non-uniform irradiation levels using Matlab,and to investigate its effectiveness adequately,the results of the proposed method are compared with those of the neural network *** experimental results show that the proposed method can decrease the interference of the local maximum power-point to cause the PV system to operate at a global maximum *** efficiency of the MPSO is achieved with the least number of steady-state oscillations under partial shading conditions compared with the neural network method.

关键词： Photovoltaic(PV) maximum power point tracking(MPPT) step-up converter artificial neural networks(ANNs) particle-swarm optimization(PSO)

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Towards Efficient Dynamic Uplink Scheduling over Multiple Unknown Channels

arXiv

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arXiv 2022年

作者： Wu, Shuang Ren, Xiaoqiang Jia, Qing-Shan Johansson, Karl Henrik Shi, Ling Huawei Noah’s Ark Lab Hong Kong The School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China The Center for Intelligent and Networked Systems Department of Automation BNRist Tsinghua University Beijing100084 China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Age-of-Information (AoI) is a critical metric for network applications. Existing works mostly address optimization with homogeneous AoI requirements, which is different from practice. In this work, we optimize uplink scheduling for an access point (AP) over multiple unknown channels with heterogeneous AoI requirements defined by AoI-dependent costs. The AP serves N users by using M channels without the channel state information. Each channel serves only one user in each decision epoch. The optimization objective is to minimize the time-averaged AoI-dependent costs plus additional communication transmission costs over an infinite horizon. This decision-making problem can be formulated as a Markov decision process, but it is computationally intractable because the size of the state space grows exponentially with respect to the number of users. To alleviate the challenge, we reformulate the problem as a variant of the restless multi-armed bandit (RMAB) problem and leverage Whittle’s index theory to design an index-based scheduling policy algorithm. We derive an analytic formula for the indices, which reduces the computational overhead and facilitates online adaptation. Our numerical examples show that our index-based scheduling policy achieves comparable performance to the optimal policy and outperforms several other heuristics. Copyright © 2022, The Authors. All rights reserved.

关键词： Optimization

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Semi-global Periodic Event-triggered Output Regulation for Nonlinear Multi-agent systems

arXiv

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arXiv 2022年

作者： Zheng, Shiqi Shi, Peng Zhang, Huiyan the School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China the School of Electrical and Electronic Engineering The University of Adelaide AdelaideSA5005 Australia the College of Engineering and Science Victoria University MelbourneVIC8001 Australia the National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective. © 2022, CC BY.

关键词： Multi agent systems

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Privacy Preservation for Cloud-Edge-Collaborative Energy Management System Using Post-Quantum Homomorphic Encryption

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IEEE Transactions on Smart Grid 2025年

作者： Jiang, Cheng Li, Xue Du, Dajun Qian, Hong Wen, Mi Wu, Lei Findeisen, Rolf Shanghai University of Electric Power Shanghai Key Laboratory of Power Station Automation Technology College of Automation Engineering Shanghai200090 China Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States TU Darmstadt Control and Cyber-Physical Systems Laboratory Darmstadt64227 Germany

Cloud-based energy management systems (EMS) in smart grids face privacy challenges, as existing methods based on traditional homomorphic encryption support limited operations and are vulnerable to quantum attacks. We propose a privacy preservation method for smart grid energy management system, leveraging edge-assisted computing and ring learning with errors (RLWE) homomorphic encryption. Our approach enables both addition and multiplication operations on encrypted smart grid data while defending against quantum threats. We demonstrate the methods security under the RLWE hardness assumption and validate its effectiveness through an experimental platform simulating smart grid environments. This work addresses computational limitations in current privacy-preserving techniques, enhancing data security for evolving smart grid technologies © 2010-2012 IEEE.

关键词： Power management (telecommunication)

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State Estimation for Linear systems with Quadratic Outputs

arXiv

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arXiv 2023年

作者： Berkane, Soulaimane Theodosis, Dionysis Hamel, Tarek Dimarogonas, Dimos V. Département d’informatique et d’ingénierie Université du Québec en Outaouis GatineauQC Canada theDepartment of Electrical Engineering Lakehead University ON Canada the Dynamic Systems and Simulation Laboratory Technical University of Crete Greece the Divi-sion of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden I3S-CNRS University Côte d’Azur Institut universitaire de France France

This letter deals with the problem of state estimation for a class of systems involving linear dynamics with multiple quadratic output measurements. We propose a systematic approach to immerse the original system into a linear time-varying (LTV) system of a higher dimension. The methodology extends the original system by incorporating a minimum number of auxiliary states, ensuring that the resulting extended system exhibits both linear dynamics and linear output. Consequently, any Kalman-type observer can showcase global state estimation, provided the system is uniformly observable. © 2023, CC BY.

关键词： Time varying systems

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Adaptive Optimal electrical Resistance Tomography for Large-Area Tactile Sensing

Adaptive Optimal Electrical Resistance Tomography for Large-...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Wendong Zheng Huaping Liu Di Guo Wuqiang Yang Department of Computer Science and Technology Tsinghua University Beijing China the State Key Laboratory of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Electronic Engineering The University of Manchester Manchester U.K.

It is critical to perceive physical contact for intelligent robots to safely interact in dynamic, unstructured environments. As physical contacts can occur at any location, a well-performing tactile sensing system should be able to deploy a large area on robotic surface. Some researchers have implemented large-area tactile sensors by using sensing arrays, but it is challenging to deploy many sensing elements. electrical resistance tomography (ERT) has recently been introduced into tactile sensing to overcome some of the limitations with conventional tactile sensing arrays, and good results have been achieved for some robotic applications. However, a particular challenge is that spatial resolution is low. Although various attempts have been made to improve the performance of ERT-based tactile sensors, the intrinsic resolution issue remains unsolved. In this paper, we propose a novel adaptive optimal drive strategy for efficient ERT-based large-area tactile sensing for robotic applications, which can adaptively select the current injection and voltage measurement pattern for optimal tactile stimulus. In particular, regions of tactile contacts are preliminarily detected and localized by a base scanning pattern with only a few measurement data. According to this detected region, the adaptive strategy can select the optimal current injection and voltage measurement pattern to improve the sensing performance by maximizing the current density. To verify the effectiveness of the proposed strategy, the proposed method is comprehensively evaluated by simulation and experiments. The results revealed that the optimal strategy can effectively improve both spatial and temporal resolution.

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Quantized Distributed Nonconvex Optimization with Linear Convergence

Quantized Distributed Nonconvex Optimization with Linear Con...

引用

IEEE Conference on Decision and control

作者： Lei Xu Xinlei Yi Jiayue Sun Yang Shi Karl Henrik Johansson Tao Yang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering University of Victoria Victoria Canada

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper considers distributed nonconvex op-timization for minimizing the average of local cost functions, by using local information exchange over undirected communication networks. Since the communication channels often have limited bandwidth or capacity, we first introduce a quantization rule and an encoder/decoder scheme to reduce the transmission bits. By integrating them with a distributed algorithm, we then propose a distributed quantized nonconvex optimization algorithm. Assuming the global cost function satisfies the Polyak– Łojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that the proposed algorithm linearly converges to a global optimal point. Moreover, a low data rate is shown to be sufficient to ensure linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical simulation examples.

关键词： Quantization (signal) Communication channels Bandwidth Cost function Numerical simulation Communication networks Distributed algorithms

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Electrochemical Detection of Lactate and Glucose with Enzyme-Free and Dual-Sensing Using Nickel-Oxide Nanoparticles

SSRN

引用

SSRN 2025年

作者： Nasiri, Rohollah Guagliano, Giuseppe Van Gastel, Dirkje Sanei, Reihaneh Madadelahi, Masoud Tanriverdi, Selim Jain, Saumey Fayazbaksh, Farzaneh Lee, Sang Won Zhu, Yangzhi Joensson, Haakan N. Russom, Aman Herland, Anna Division of Nanobiotechnology Department of Protein Science Science for Life Laboratory KTH Royal Institute of Technology Solna Sweden AIMES Center for the Advancement of Integrated Medical and Engineering Sciences Department of Neuroscience Karolinska Institute Solna Sweden Department of Chemistry Materials and Chemical Engineering "G. Natta" Politecnico di Milano Milan Italy Division of Micro and Nanosystems Department of Intelligent Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Terasaki Institute for Biomedical Innovation Los AngelesCA90064 United States

Detection and monitoring of lactate and glucose levels in biological fluids and cell cultures are critical for understanding metabolic disorders. While electrochemical biosensors are commonly used, traditional enzymatic sensors face stability, reproducibility, and cost challenges. To address these issues, we developed non-enzymatic sensors using nanostructured electrodes, specifically nickel oxide (NiO)-based, for lactate and glucose detection. The sensors were fabricated by drop-casting a NiO/Nafion/ethanol dispersion onto the working electrode, with performance evaluated through cyclic voltammetry and amperometry. Optimal sensitivity and linearity were achieved at a working voltage of ~0.5 V. To address glucose interference, sensors were modified with Prussian Blue, creating a dual sensor for lactate and glucose. The sensors respectively exhibited linear responses for lactate (0.1 – 5 mM) and glucose (0.1 – 5 mM) with detection limits of 0.60 mM and 0.35 mM, and it showed sensitivities of 0.43 ± 0.05 µA/mM (lactate) and 0.82 ± 0.02 µA/mM (glucose) in phosphate buffer solution. Validation against the lactate and glucose assay kits in a cell culture medium showed good agreement, highlighting the potential of these enzyme-free electrochemical sensors for metabolic analysis. Finally, the sensor was integrated with a microfluidic device, demonstrating its potential as a flow-through, enzyme-free metabolic sensor for future organ-on-chip applications. © 2025, The Authors. All rights reserved.

关键词： Cyclic voltammetry

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Distributed identification of power system network branch events

Distributed identification of power system network branch ev...

引用

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Madurasinghe, Dulip Arunagirinathan, Paranietharan Venayagamoorthy, Ganesh K. Clemson University Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering ClemsonSC29634 United States School of Engineering University of Kwazulu-Natal Durban4041 South Africa

ISBN: (纸本)9781728155081

Online identification of power system network branches is critical in modern electric power system operation. Availability of phasor measurement units (PMUs) can be used to identify branch events. Due to complexity of the power system, a distributed cellular computational network (CCN) is proposed. Comparison of centralized and distributed neural network based power system network branch events identification is studied. IEEE 12-bus benchmark power system is simulated on real-time digital simulator platform for this study. CCN based distributed neural network approach is computationally efficient compared to centralized approach. © 2020 IEEE.

关键词： Phasor measurement units

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Deep Feature Pyramid Network for Eeg Emotion Recognition

SSRN

引用

SSRN 2022年

作者： Hou, Fazheng Gao, Qiang Song, Yu Wang, Zhe Bai, Zhongli Yang, Yi Tian, Zekun School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin University of Technology Tianjin300384 China TUT Maritime College Tianjin University of Technology Tianjin300384 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

In this work, the Feature Pyramid Network (FPN) is proposed for improving the performance of electroencephalography (EEG) emotion recognition. Specifically, the Differential Entropy (DE) is extracted as a basic feature, and we adopt bi-harmonic spline interpolation to interpolate the features maps according to real 3D electrode spatial information. The spatial information is obtained to avoid the loss of effective information. Next, the proposed FPN is applied to fuse multiscale EEG spatial information for obtaining the deeper semantic features, which avoid blind self-learning of deep convolutional neural networks. Finally, a Support Vector Machine (SVM) is utilized to predict the emotional state. The experiment results of our method has a state-of-the-art performance by 70-30 cross-validation with the mean accuracy of 96.97% for arousal and 94.29% for valence on the DEAP database. And the accuracy rate of 97.12% on the SEED database also proves the generalization of the proposed method. © 2022, The Authors. All rights reserved.

关键词： Speech recognition

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