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CPSS Transactions on Power Electronics and Applications 2024年第1期9卷 51-62页

作者： Gao, Chao Zhang, Shuyu Lu, Bo Ding, Wenlong Leung, Ka Nang Loh, Poh Chiang The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong School of Engineering Stanford University StanfordCA94305 United States Academy for Engineering and Technology Fudan University Shanghai200433 China School of Control Science and Engineering Shandong University Jinan250100 China

PR controller has been widely researched in various control systems for its robustness and simplicity. However, a traditional PR controller with relatively small integral gain, used for higher-order harmonics to keep stability, will cause increases in magnitudes, and decreases in phase around resonant frequency, and jeopardize stability. These all call for a more precise realization of PR controller. This paper proposes a cascade-formed PR controller realization method, which proves to realize PR controller more accurately even with a relatively small integral gain. The method is to decompose a PR controller into multiple independent PR units, and each PR unit is realized by mapping PR controller's parameters to its pole and zero positions. The distance between a pole-zero pair is found related to frequency characteristic error and is restricted accordingly to limit the error. Comprehensive comparisons of PR controllers realized by cascade form and the traditional parallel form have been conducted theoretically and experimentally, verifying that the cascade realization method is more accurate. © 2017 CPSS.

关键词： controllers

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Economic Optimal Scheduling of Integrated Energy System Based on Improved DQN Algorithm 1st

Economic Optimal Scheduling of Integrated Energy System Base...

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1st Electrical Artificial Intelligence Conference, EAIC 2024

作者： Ye, Ning Li, Ke Wang, Xuerui Wang, Haiyang Zhang, Chenghui School of Control Science and Engineering Shandong University Shandong Province Jinan250061 China

ISBN: (纸本)9789819648559

Integrated energy systems have a significant role and non-negligible importance in modern energy systems. In order to improve the operating economy of the integrated energy system and at the same time to cope with the challenges brought by multiple uncertainties within the system, an economic scheduling model of the integrated energy system is proposed and solved by deep reinforcement learning method. Firstly, the optimal scheduling problem of the integrated energy system is mathematically modeled;secondly, it is converted into the expression form of Markov decision process, and the state, action space and reward function are established;after that, the DQN algorithm is improved to increase the training speed and stability of the algorithm, and the optimal scheduling problem is solved with the goal of economy. Finally, the effectiveness and superiority of the proposed method in optimized scheduling of integrated energy systems are verified through arithmetic simulation and comparison with traditional algorithms. © The Author(s) 2025.

关键词： Scheduling algorithms

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Fault identification of rotating machinery based on multiscale convolution and deep residual networks 9

Fault identification of rotating machinery based on multisca...

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9th International Symposium on Sensors, Mechatronics, and Automation System, ISSMAS 2023

作者： Wang, Huihui Fan, Tianqi Qiu, Sen Liu, Long School of Intelligence and Electronic Engineering Dalian Neusoft University of Information Dalian116023 China Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education The School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9781510672802

Rotating machinery and equipment have a wide range of industrial applications, and it is important to perform intelligent fault detection during their operation. In order to fully capture the multi-scale features of mechanical fault data while solving the degradation problem of deep networks, we propose an intelligent fault detection model combining multi-scale convolution and deep residual networks. We validate it on four publicly available datasets, and the results demonstrate the excellent performance of the proposed method. © 2024 SPIE.

关键词： Convolution Feature extraction Deep learning Machine learning Vibration Data modeling Lithium Convolutional neural networks Data centers Signal processing

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Numerical study on two-phase boiling heat transfer performance of interrupted microchannel heat sinks

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science China(Technological sciences) 2022年第3期65卷 679-692页

作者： ZHOU JianHong CHEN XueMei LI Qiang MIIT Key Laboratory of Thermal Control of Electronic Equipment School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China

The conventional straight microchannel heat sinks have been reported to inadequately remove the increasing power density of *** recent years,an effective heat transfer enhancement method,flow disruptions have attracted the attention of researchers,where interrupted structures are arranged in the microchannel to enhance flow mixing and heat ***,previous numerical studies of interrupted microchannel heat sinks(I MCHS)mainly focus on single-phase flow condition,and the characteristics of the boiling heat transfer of I MCHS in two-phase flow condition have been rarely ***,the flow and heat transfer characteristics of two I MCHS based on rectangular microchannel heat sink(R MCHS)are investigated by modeling both single-phase and two-phase flow *** two interrupts consist of a combination of cavities and ribs,namely elliptical cavities and elliptical side ribs(EC-ESR),and elliptical cavities and elliptical central ribs(EC-ECR).The results show that for single-phase flow condition,the maximum Nusselt number is increased by 187%in the EC-ESR design and150%in the EC-ECR design compared with the R *** subcooled boiling(i.e.,two-phase flow)condition,the EC-ECR design is a promising structure to enhance boiling heat transfer with 6.7 K reduction of average wall temperature and 29%increment of local heat transfer coefficient when compared with those of R ***,the local heat transfer coefficient in the EC-ESR design is decreased by 22%compared with the R MCHS due to the formation of a rare flow pattern(i.e.,inverted annular flow with vapor film separation)in the *** flow pattern can induce departure from nucleate boiling(DNB),thereby deteriorating the heat transfer on the channel walls.

关键词： microchannel heat sink cavities and ribs thermal performance flow pattern boiling heat transfer flow disruptions

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An Improved YOLOv5s-Based Smoke Detection System for Outdoor Parking Lots

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Computers, Materials & Continua 2024年第8期80卷 3333-3349页

作者： Ruobing Zuo Xiaohan Huang Xuguo Jiao Zhenyong Zhang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China Key Laboratory of Computing Power Network and Information Security Ministry of EducationQilu University of Technology(Shandong Academy of Sciences)Jinan250353China Text Computing&Cognitive Intelligence Engineering Research Center of National Education Ministry Guizhou UniversityGuiyang550025China

In the rapidly evolving urban landscape,outdoor parking lots have become an indispensable part of the city’s transportation *** growth of parking lots has raised the likelihood of spontaneous vehicle combus-tion,a significant safety hazard,making smoke detection an essential preventative ***,the complex environment of outdoor parking lots presents additional challenges for smoke detection,which necessitates the development of more advanced and reliable smoke detection *** paper addresses this concern and presents a novel smoke detection technique designed for the demanding environment of outdoor parking ***,we develop a novel dataset to fill the gap,as there is a lack of publicly available *** dataset encompasses a wide range of smoke and fire scenarios,enhanced with data augmentation to ensure robustness against diverse outdoor ***,we utilize an optimized YOLOv5s model,integrated with the Squeeze-and-Excitation Network(SENet)attention mechanism,to significantly improve detection accuracy while maintaining real-time processing ***,this paper implements an outdoor smoke detection system that is capable of accurately localizing and alerting in real time,enhancing the effectiveness and reliability of emergency *** show that the system has a high accuracy in terms of detecting smoke incidents in outdoor scenarios.

关键词： YOLOv5s smoke detection deep learning SENet

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Phase transformation of Cr(Ⅵ)-adsorbed ferr ihydr ite in the presence of Mn(Ⅱ): Fate of Mn(Ⅱ)and Cr(Ⅵ)

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Journal of Environmental sciences 2022年第3期34卷 251-259页

作者： Zecong Ding Guangzhao Sun Fenglian Fu Chujia Ye School of Environmental Science and Engineering Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlGuangdong University of TechnologyGuangzhou 510006China

Ferrihydrite is an important sink for the toxic heavy metal ions, such as Cr(Ⅵ). As ferrihydrite is thermodynamically unstable and gradually transforms into hematite and goethite, the stability of Cr(Ⅵ)-adsorbed ferrihydrite is environmentally significant. This study investigated the phase transformation of Cr(Ⅵ)-adsorbed ferrihydrite at different pH in the presence of aqueous Mn(Ⅱ), as well as the fate of Mn(Ⅱ) and Cr(Ⅵ) in the transformation process of ferrihydrite. Among the ferrihydrite transformation products, hematite was dominant, and goethite was minor. The pre-adsorbed Cr(Ⅵ) inhibited the conversion of ferrihydrite to goethite at initial pH 3.0, whereas little amount of adsorbed Mn(Ⅱ) favored the formation of goethite at initial pH 7.0. After the aging process, Cr species in solid phase existed primarily as Cr(Ⅲ) in the presence of Mn(Ⅱ) at initial pH 7.0 and 11.0. The aqueous Mn concentration was predominantly unchanged at initial pH 3.0, whereas the aqueous Mn(Ⅱ) was adsorbed onto ferrihydrite or form Mn(OH)_(2) precipitates at initial pH 7.0 and 11.0, promoting the immobilization of Cr(Ⅵ). Moreover, the oxidation of Mn(Ⅱ) occurred at initial pH 7.0 and 11.0, forming Mn(Ⅲ/Ⅳ)(hydr)oxides.

关键词： Ferrihydrite Phase transformation Gr(Ⅵ)adsorption and reduction Mn(Ⅱ)adsorption and oxidation

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Domain Adapted Object Detection with Intermediate Domain Generation 21

Domain Adapted Object Detection with Intermediate Domain Gen...

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21st International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Yuhang, He Yangyang, Sun Zhijun, Xue Shijiao, Han School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (纸本)9798331519254

Autonomous driving detection technology in real-world road scenarios faces numerous challenges, including variable weather conditions and complex road environments. Therefore, developing an object detection model with robust domain adaptation is crucial. In this paper, we investigate the use of image style transfer techniques to leverage target domain images for enhancing model performance. Experimental results show that our proposed approach significantly improves detection efficacy. Notably, our method outperforms the Oracle results in tasks such as transitioning from Cityscapes to Foggy Cityscapes, highlighting its effectiveness in addressing domain adaptation challenges. © 2024 IEEE.

关键词： Image enhancement

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Adaptive Iterative Learning control for Nonlinear Multiagent Systems With Initial Error Compensation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4192-4201页

作者： Li, Zhiqiang Zhou, Qi Liu, Yang Ren, Hongru Li, Hongyi Guangdong University of Technology School of Automation and Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Qingdao University of Science and Technology School of Automation and Electronics Engineering Qingdao266061 China

In this article, the consensus tracking problem of neural network (NN)-based adaptive iterative learning control (AILC) scheme is investigated for the nonlinear multiagent systems (MASs) with repetitive control tasks. To achieve the better tracking performance, the NN is developed to iteratively learn the uncertain nonlinearity. Meanwhile, the gradient descent algorithm is utilized to train NN weights, which is different from the traditional method based on \sigma-modification. For initial error problems of AILC, an initial error compensation method is developed to deal with the initial consensus tracking error. During the AILC design using the dynamic surface control technique, an auxiliary control signal is introduced to handle the residual term. Then, the boundedness of all signals and the iterative convergence of tracking errors are analyzed by the Lyapunov theory. Final, a simulation of the multimanipulators is provided to validate the effectiveness of the proposed control algorithm. © 2020 IEEE.

关键词： Multi agent systems

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Multi-objective optimization of lithium-ion battery designs considering the dilemma between energy density and rate capability

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Energy and AI 2024年第4期18卷 53-63页

作者： Xiao-Ying Ma Wen-Ke Zhang Ying Yin Kailong Liu Xiao-Guang Yang National Engineering Research Center of Electric Vehicles School of Mechanical EngineeringBeijing Institute of TechnologyBeijing100081China Shenzhen Automotive Research Institute Beijing Institute of TechnologyShenzhen518118GuangdongChina School of Control Science and Engineering Shandong UniversityJinan250100China

Electrified transportation requires batteries with high energy density and high-rate capability for both charging and ***-ion batteries(LiBs)face a dilemma:increasing areal capacity and reducing electrode porosity to boost energy density often reduces rate capability due to a longer and more tortuous ion transfer *** cell design parameters to balance these metrics is essential but ***,we present a multi-objective optimization framework targeting energy density,fast charging,high-rate discharging,and lifespan *** cell parameters-cathode areal capacity,N-P ratio,cathode porosity,and anode poros-ity-along with operating temperature,are selected as design variables.A physics-based pseudo-2D model,validated against experimental data,generates data to train the surrogate model,which is combined with the NSGA-Ⅱalgorithm for rapid *** different objective calculation methods are compared to identify the maximum sum of energy densities,lowest polarization,and most balanced performance,*** design parameters are optimized at different temperatures using the most balanced optimization *** demonstrate that elevating cell operating temperature achieves high-rate capability while maintaining high energy density,mitigating the energy-power trade-off and broadening battery design parameter ranges.

关键词： Lithium-ion batteries Multi-objective optimization Battery design Fast charging Lithium plating

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Event-triggered Adaptive Penalty Model Predictive control for Hybrid Energy Storage System 3

Event-triggered Adaptive Penalty Model Predictive Control fo...

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3rd International Conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Wang, Siqi Li, Zihao Guo, Yuchao Fan, Yuan Anhui University School of Electrical Engineering and Automation Anhui Hefei China Zhejiang University College of Control Science and Engineering Zhejiang Hangzhou China

ISBN: (纸本)9798350352658

This work proposes an optimized voltage stabilization approach for electric vehicles (EVs) integrated with PV systems and a hybrid energy storage system (HESS). Specifically, the combination of Adaptive Penalty Model Predictive control (APMPC) and an Event-triggered (ET) mechanism is utilized to effectively regulate the PV output and storage response when the solar irradiance increases suddenly. This approach dynamically adjusts the operation of system to maintain a stable DC bus voltage. Simulations validate the effectiveness of the proposed method in stabilizing the voltage and improving energy utilization, thereby contributing to the development of sustainable and efficient EVs systems. © 2024 IEEE.

关键词： Predictive control systems

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