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A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction

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Green Energy and Intelligent Transportation 2024年第2期3卷 50-59页

作者： Yuan Chen Wenxian Duan Yigang He Shunli Wang Carlos Fernandez School of Artificial Intelligence Anhui UniversityHefei 230009China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430000China School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China School of Pharmacy and Life Sciences Robert Gordon UniversityAberdeenAB10-7GJUK

Battery life prediction is of great significance to the safe operation,and reduces the maintenance *** paper proposes a hybrid framework considering feature extraction to achieve more accurate and stable life prediction performance of the *** feature extraction,eight features are obtained to fed into the life prediction *** hybrid framework combines variational mode decomposition,the multi-kernel support vector regression model and the improved sparrow search algorithm to solve the problem of data backward,uneven distribution of high-dimensional feature space and the local escape ability,*** parameters of the estimation model are obtained by introducing the elite chaotic opposition-learning strategy and adaptive weights to optimize the sparrow search *** algorithm can improve the local escape ability and convergence performance and find the global *** comparison is conducted by dataset from National Aeronautics and Space Administration which shows that the proposed framework has a more accurate and stable prediction *** with other algorithms,the SOH estimation accuracy of the proposed algorithm is improved by 0.16%–1.67%.With the advance of the start point,the RUL prediction accuracy of the proposed algorithm does not change much.

关键词： State of heath Improved sparrow search algorithm Remaining useful life Variational mode decomposition Multi-kernel support vector regression Feature extraction

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The Study of RWENN for Proton Exchange Membrane Fuel Cell System in Microgrid 2

The Study of RWENN for Proton Exchange Membrane Fuel Cell Sy...

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2nd International Symposium on electrical, Electronics and Information engineering, ISEEIE 2022

作者： Lu, Kai-Hung Yiping, Deng Zhimin, Li Ziyu, Xu Yunhao, Chen Junfang, Lian Xia, Yang School of Electronic and Electrical Engineering Minnan University of Science and Technology Fujian Key Laboratory of Industrial Automation Control Technology and Information Processing Fujian Quanzhou China School of Electrical and Automation Engineering East China Jiaotong University Jiangxi Nanchang China

ISBN: (数字)9781665468749

ISBN: (纸本)9781665468749

Fuel cells are an effective use of clean energy. It has strong controllability, low operating noise and low heat radiation. This is one of the important development directions for future service-oriented computing and power supply. Them, proton exchange membrane fuel cell (PEMFC) has become a research hotspot in this field because of its high power, low operating temperature, fast start-up and long life. This paper studies the PEMFC power generation system in microgrid by Recurrent Wavelet-based Elman neural network (RWENN). The PEMFC power system is integrated into the distribution network by AC/DC. The microgrid is designed from the hierarchical structure of the fuel cell microgrid system. The effectiveness of the RWENN control strategy is verified by modeling and simulation analysis in this paper. © 2022 IEEE.

关键词： Protons Analytical models Power supplies Heuristic algorithms Power system dynamics Neural networks Fuel cells

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A Novel Cross-Ratio Based Gaze Estimation Method

A Novel Cross-Ratio Based Gaze Estimation Method

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2022 International Conference on Machine Learning and Knowledge engineering, MLKE 2022

作者： Fan, Shuo Chi, Jiannan Liu, Jiahui University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665495677

Eye movement is the most natural expression of human thoughts, therefore it plays an important role in human-computer interaction. Over the past few decades, researchers have been pursuing for high-accuracy, easy-to-use eye-tracking techniques. The gaze tracking technology based on cross-ratio is a hot topic in the field due to its advantages of simple hardware device and allowing free head movement. Given the complexity of the user calibration procedure and the error caused by the coplanar assumption in the cross-ratio based method, we propose a new method to approximate the pupil plane step by step through constructing the front and rear planes, and then estimate the point-of-regard based on cross-ratio invariance. Simulation results show that the proposed method not only simplifies the system configuration and user calibration procedure, but also avoids the error caused by the non-coplanarity between the corneal surface reflection points and the pupil center. © 2022 IEEE.

关键词： Eye tracking

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Distributed Cooperative control for Human-Unmanned Aerial Vehicle Swarm Teaming in Target Tracking*

Distributed Cooperative Control for Human-Unmanned Aerial Ve...

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IEEE International Conference on Robotics and Biomimetics

作者： Hangxuan He Mengzhen Huo Haibin Duan School of Automation Science and Electrical Engineering Beihang University Beijing PR China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing PR China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Over the last decade, the relationship between humans and cyber-physical systems has grown closer, particularly in fields such as manufacturing and transportation. This paper presents a control framework within the engineering domain, wherein a human operator collaborates with a swarm of unmanned aerial vehicles (UAVs) to achieve a shared goal. First, we construct a human-swarm mutual trust model that empowers both parties with a degree of autonomy. Second, we adopt a distributed optimization algorithm integrated with control barrier functions to manage the swarm's motion. The cooperative control framework is demonstrated in a 3D scenario, and simulation results verify the feasibility of the proposed method.

关键词： Three-dimensional displays Target tracking Simulation Transportation Collaboration Cyber-physical systems Autonomous aerial vehicles Manufacturing Optimization Robots

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A Differential Game Approach to Collision Avoidance in Multi-Agent Systems 41

A Differential Game Approach to Collision Avoidance in Multi...

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第41届中国控制会议

作者： Wenyan Xue Zhihong Wu Siyuan Zhan Yutao Chen Jie Huang College of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Department of Electronic Engineering Maynooth University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper gives a novel differential game scheme to solve the collision avoidance problem for multi-agent *** on the concept of artificial potential field(APF),we combine obstacle avoidance objectives with trajectory optimization targets as the performance *** feedback strategies are based on the solutions of coupled Riccati ***,it is proved that the feedback strategies will converge to a Nash equilibrium(NE).Finally,simulation results are provided to show the advantages,which make agents arrive at the targeted position collision-free with a reduced time.

关键词： Collision avoidance differential game trajectory optimization Nash equilibrium

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Optimization for Pickup Vehicle Scheduling in Steel Logistics Park Based on Enhanced SPEA2

Optimization for Pickup Vehicle Scheduling in Steel Logistic...

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2023 China automation Congress, CAC 2023

作者： Xu, Hongjie Wang, Jinlong Xu, Zhezhuang Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd. Sanming353000 China

ISBN: (纸本)9798350303759

Pickup vehicle scheduling in the steel logistics park is a critical issue in determining the outbound effciency of steel products. Steel products are distributed in the yards of the steel logistics park with mixed storage, and the optional yards for each pickup operation are not unique, which greatly increases the scheduling complexity. To overcome this challenge, in this paper, we propose a pickup vehicle scheduling problem with mixed steel storage (PVSP-MSS) to optimize makespan of pickup vehicle and makespan of steel logistics park simultaneously. The optimization problem is described as a multi-objective problem, and an enhanced Strength Pareto Evolutionary Algorithm 2 (ESPEA) is proposed to solve the problem with high efficiency. Experiments are executed based on data collected from a real steel logistics park. The results confirm that ESPEA can significantly reduce both makespan of each pickup vehicle and makespan of steel logistics park. © 2023 IEEE.

关键词： Pickups

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State-of-Charge (SOC) Estimation of Lithium-Ion Battery Based on Unscented Kalman Filtering 6

State-of-Charge (SOC) Estimation of Lithium-Ion Battery Base...

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6th IEEE Advanced Information Management, Communicates, Electronic and automation control Conference, IMCEC 2024

作者： Miao, Mengfan Li, Ligang Wang, Zhongfeng Jiang, Jing Shenyang Ligong University College of Automation and Electrical Engineering Liaoning China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9798350316520

Real-time estimation of State of Charge (SOC) for lithium-ion batteries is one of the core technologies in Battery Management Systems (BMS). Accurate SOC estimation is fundamental for managing lithium-ion batteries. In this study, a second-order RC equivalent circuit model is established, and parameter identification methods are employed to determine the model parameters. The identified parameters are then incorporated back into the second-order RC model. The accuracy of these parameters and the model is validated through Hybrid Pulse Power Characteristic (HPPC) tests. Finally, the Unscented Kalman Filtering algorithm (UKF) is utilized to estimate battery SOC. Experimental results demonstrate that SOC estimation based on UKF exhibits high precision and stability. © 2024 IEEE.

关键词： Lithium-ion batteries

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Quasi-Z Source Inverter control of PV Grid-Connected Based on Fuzzy PCI

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Journal of Electronic Science and Technology 2021年第3期19卷 274-286页

作者： Tao Hou Chen-Yang Zhang Hong-Xia Niu School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou 730070 Automatic Control Research Institute Lanzhou Jiaotong UniversityLanzhou 730070

The photovoltaic grid-connected inverter is an important interface between the photovoltaic power generation system and power *** high-quality operation is directly related to the output power quality of the power *** order to further optimize the control effect of the quasi-Z source grid-connected photovoltaic inverter,a fuzzy proportional complex integral control(PCI)method is proposed for the current internal loop *** method can eliminate the steady-state error,and has the characteristic of zero steady-state error adjustment for the AC disturbance signal of a specific *** inductance-capacitance-inductance(LCL)filter is adopted in the grid-connected circuit,and the feedback capacitive current is taken as the control variable of the inner loop to form the active damping control method,which can not only effectively suppress the resonance of the LCL circuit,but also significantly inhibit the high-order harmonics in the grid-connected ***,a system simulation model is built in MATLAB/Simulink to verify the superiority and effectiveness of the proposed method.

关键词： Frequency of harmonic distortion fuzzy proportional complex integral inductance-capacitance-inductance(LCL)filtering circuit photovoltaic grid-connection quasi-Z source inverter

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Stability and performance analysis of the compressed Kalman filter algorithm for sparse stochastic systems

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Science China(Technological Sciences) 2024年第2期67卷 380-394页

作者： LI RongJiang GAN Die XIE SiYu LüJinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Zhongguancun Laboratory Beijing 100049China School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu 611731China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

This paper considers the problem of estimating unknown sparse time-varying signals for stochastic dynamic *** deal with the challenges of extensive sparsity,we resort to the compressed sensing method and propose a compressed Kalman filter(KF)*** algorithm first compresses the original high-dimensional sparse regression vector via the sensing matrix and then obtains a KF estimate in the compressed low-dimensional ***,the original high-dimensional sparse signals can be well recovered by a reconstruction *** ensure stability and establish upper bounds on the estimation errors,we introduce a compressed excitation condition without imposing independence or stationarity on the system signal,and therefore suitable for feedback *** further present the performance of the compressed KF ***,we show that the mean square compressed tracking error matrix can be approximately calculated by a linear deterministic difference matrix equation,which can be readily evaluated,analyzed,and ***,a numerical example demonstrates that our algorithm outperforms the standard uncompressed KF algorithm and other compressed algorithms for estimating high-dimensional sparse signals.

关键词： sparse signal compressed sensing Kalman filter algorithm compressed excitation condition stochastic stability tracking performance

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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