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Chinese control Conference (CCC)

作者： Huangyuwei Lu Zuo Wang Jiankun Sun Xi Xiao Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Nanjing China Shenzhen Research Institute Southeast University Shenzhen China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing China

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators, a composite iterative learning control (ILC) scheme via generalized proportional integral observer (GPIO) is proposed. A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics, parameter uncertainties and load fluctuations. A GPIO is then designed to estimate the disturbances and high-order time derivatives. By introducing estimations into a PD-type ILC at each iteration, a composite control scheme is obtained, such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of manipulators. In this paper, the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to infinity. The effectiveness of the proposed control scheme is finally verified by simulation results.

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Predefined-Time Synchronization of Inertial Memristive Neural Networks

Predefined-Time Synchronization of Inertial Memristive Neura...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Zeng, Kan Wang, Leimin School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781665412872

This article investigates the predefined-time synchronization (PTS) of inertial memristive neural networks (IMNNs). First, we reduce the order of the system and design an effective controller for the error system. Furthermore, several new criteria for PTS of IMNNs are obtained and a user-defined settling time is provided. Lastly, the effectiveness of the results is proved by simulation experiment. © 2021 IEEE.

关键词： Synchronization

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Emission and optical characteristics of brown carbon in size-segregated particles from three types of Chinese ships

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Journal of Environmental Sciences 2024年第8期142卷 248-258页

作者： Fengqin Yang Fan Zhang Zeyu Liu Yingjun Chen Yan Zhang Can Wu Yali Lei Shijie Liu Binyu Xiao Xinyi Wan Yubao Chen Yong Han Min Cui Cheng Huang Gehui Wang Key Lab of Geographic Information Science of the Ministry of Education School of Geographic SciencesEast China Normal UniversityShanghai 200241China Institute of Eco-Chongming 20 Cuiniao Rd.ChongmingShanghai 202150China State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex Shanghai Academy of Environmental SciencesShanghai 200233China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 200438China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China Department of Civil and Environmental Engineering and State Key Laboratory of Marine Pollution The Hong Kong Polytechnic UniversityKowloon 100872Hong KongChina College of Environmental Science and Engineering Yangzhou UniversityYangzhou 225009China

Brown carbon(BrC)is one of the important light absorption substances that have high light absorption ability under short wavelength ***,limit studies have focused on the BrC emission from *** this study,size-segregated particulate matters(PM)were collected from three different types of ships,light absorption characteristics and size distribution of methanol-soluble BrC and water-soluble BrC in PM from ship exhausts were *** showed that four-stroke low-power diesel fishing boat(4-LDF)had the highest mass concentrations of methanol-soluble organic carbon(MSOC)and water-soluble organic carbon(WSOC),followed by 2-stroke high-power heavy-fuel-oil vessel(2-HHV),and fourstroke high-power marine-diesel vessel(4-HMV).While 2-HHV had obviously higher light absorption coefficients of methanol-soluble BrC(Abs365,M)and water-soluble BrC(Abs365,W)in unit weight of PM than the other two types of *** tested ships presented comparable or higher absorption efficiency of BrC in water extracts(MAE365,W)compared with other BrC emission *** of BrC was concentrated in fine particles,and the particle size distributions of both Abs365,Mand Abs365,Wshowed bimodal patterns,peaking at0.43–0.65μm and 4.7–5.8μm,***,different particle size distributions were found for MAE365,Mbetween diesel and heavy fuel oil ***,different wavelength dependence in particles with different size were also *** exhaust could be confirmed as a non-ignorable BrC emission source,and complex influencing factor could affect the light absorption characteristics of ship *** size should also be considered when light absorption ability of BrC was evaluated.

关键词： Ship emission Brown carbon Light absorption Size distribution

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Consensus-based Distributed Augmented Lagrangian Method for Nonconvex Optimization with Coupled Constraints

Consensus-based Distributed Augmented Lagrangian Method for ...

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Chinese Automation Congress (CAC)

作者： Yanxu Su School of Artificial Intelligence Anhui University Hefei P. R. China Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Southeast University Nanjing P. R. China

Abstract: In this paper, we study the nonconvex optimization problems with consideration of globally coupled constraints. The constrained optimization problem is converted into an augmented Lagrangian function, and a distributed primal-dual algorithm is exploited in the context of finite-time consensus for solving such a problem. Particularly, we do not require the globally coupled constraints to be separable. Instead, we introduce some local variables for estimating the constraint violations. Under some mild assumptions in the research of nonconvex optimization, we prove the convergence of the presented algorithm to a KKT point of the problem. The numerical experiment verifies the correctness and the effectiveness of the theoretical results.

关键词： Automation Heuristic algorithms Aggregates Numerical simulation Linear programming Optimization Lagrangian functions

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Radar Vital Signs Detection Method Based on Variational Mode Decomposition and Wavelet Transform

Radar Vital Signs Detection Method Based on Variational Mode...

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2021 China Automation Congress, CAC 2021

作者： Ma, Shaopeng Xue, Wei Chen, Kehui Wang, Zexi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

To deal with noise interference in frequency modulated continuous wave (FMCW) radar vital signs and the interference of breathing harmonics on the heartbeat signal, a vital signs detection method based on variational mode decomposition (VMD) and wavelet transform is proposed. First, VMD is applied to decompose the vital signs into a series of intrinsic mode function (IMF) components. Then, the IMF components with spectral peaks in the frequency range of breathing and heartbeat are selected to reconstruct the breathing and heartbeat signals respectively. Finally, the wavelet transform threshold method is used to remove the noise in the breathing and heartbeat signals. The experimental results show the proposed method can overcome the influence of breathing harmonics, accurately extract the breathing and heartbeat signals, and effectively improve the signal-to-noise ratio and detection accuracy of heart rate. © 2021 IEEE

关键词： Variational mode decomposition

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Uniform Stability of Fractional-order Memristive Neural Networks with Hybrid Time-Varying Delays

Uniform Stability of Fractional-order Memristive Neural Netw...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Hu, Xiaofang Wang, Leimin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665412872

This article discusses the uniform stability of Caputo fractional-order memristive neural networks (FMNNs) with discrete delay and distributed delay. By virtue of fractional-order Razumikhin-type theorem, interval matrix method, differential inclusion and set-valued mapping, a LMI-based standard is acquired to certify uniform stability of the addressed FMNNs. Lastly, the validity of the constructed criterion is manifested by an example. © 2021 IEEE.

关键词： Time delay

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Automatic Target Recognition in GPR Images Based on Time-Frequency Texture Features and Support Vector Machine

Automatic Target Recognition in GPR Images Based on Time-Fre...

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2021 China Automation Congress, CAC 2021

作者： Chen, Kehui Xue, Wei Wang, Zexi Ma, Shaopeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

Ground penetrating radar (GPR) images are easily disturbed by noise, which causes a lot of difficulties for target recognition. To improve the target recognition performance in GPR images, a novel recognition method based on time-frequency texture features and support vector machine (SVM) is proposed. The proposed method first extracts texture features from the gray co-occurrence matrix of S transform time-frequency images for the A-scan data, then establishes the SVM model and realizes the target recognition. The proposed method is assessed using synthetic GPR images and compared with other two time-frequency analysis methods, combined with SVM. The expermental results show that the proposed method can achieve higher recognition accuracies than the other two methods in heavily noisy environment. © 2021 IEEE

关键词： Support vector machines

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control Barrier Function-Based Force Constrained Safety Compliance control for Manipulator

Control Barrier Function-Based Force Constrained Safety Comp...

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International Conference on Automation and Computing (ICAC)

作者： Haiyan Liang Xinming Wang Jianliang Mao Jun Yang The Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China College of Automation Engineering Shanghai University of Electric Power Shanghai PR China Department of Aeronautical and Automotive Engineering Loughborough University Loughborough UK

In this paper, a safety-critical compliance control with force constraint is proposed for the interaction task of a manipulator in the Cartesian space. Different from the conventional impedance control approach, the interaction force constraint is considered and interpreted by designing a new Force Constrained control Barrier Function (FCCBF) with exploiting the environment model. By formulating and solving a quadratic programming with modifying the baseline impedance controller under the FCCBF constraint, the proposed controller can not only make manipulator's interaction process satisfy expected compliance without exceeding permissible contact force range, but can also improve the dynamic characteristics of the system by eliminating force overshooting phenomena. Furthermore, with using the technique of nonlinear disturbance observer, a force sensor-less FCCBF approach is also provided, where the contact force is treated as an external disturbance. Finally, the effectiveness of the proposed algorithms is verified by both simulations and experimental tests on a 6 degree-of-freedom manipulator.

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Short-term power load forecasting during the COVID-19 pandemic using XGBoost and Copula theory

Short-term power load forecasting during the COVID-19 pandem...

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2021 China Automation Congress, CAC 2021

作者： Liu, Bo-Wen Xu, Da He, Yong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665426473

The global coronavirus disease (COVID-19) has brought great challenges to the power systems due to its limitations on social, economic and productive activities. This paper proposes a short-term load forecasting method during COVID-19 pandemic based on copula theory and eXtreme Gradient Boosting (XGBoost). In this method, the coupling relationship among the cross-domain meteorological, public health, and mobility time-series data are fully analyzed based on copula theory, which is used for the short-term power load forecasting based on multi-factor fusion XGBoost algorithm. The proposed method has been fully evaluated and benchmarked on available cross-domain open-access United States data to demonstrate its effectiveness and superiority on short-term load forecasting of COVID-19. © 2021 IEEE

关键词： COVID-19

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Real-time Semantic Segmentation of Solar Photovoltaic Arrays for Autonomous UAV Flights

Real-time Semantic Segmentation of Solar Photovoltaic Arrays...

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第43届中国控制会议

作者： Nanyan Li Hao Chen Zhigang Sun Jing Gao Dewei Yi Cunjia Liu Jinya Su School of Automation Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University State Grid Jiangsu Integrated Energy Service Co. Ltd. Department of Computing Science University of Aberdeen Department of Aeronautical and Automotive Engineering Loughborough University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper considers the real-time semantic segmentation of solar PhotoVoltaic(PV) arrays using down-facing cameras onboard Unmanned Aerial Vehicles(UAVs) to support autonomous navigation for ultra-low altitude industrial inspection. Various semantic segmentation algorithms, including SegNet, UNet, Deeplabv3+, and their respective variants, are compared to identify the most suitable one that strikes a balance between segmentation and real-time performance. Subsequently, each video frame is processed by the selected segmentation network to create a solar array mask. This mask is then optimally fitted to diverse solar array shapes to determine angular and horizontal deviations between the image center and the solar array center-line. The algorithms are validated on a self-constructed dataset of 594 solar PV array UAV images, encompassing varied environmental conditions and solar farm layouts. The top-performing network, lightweight vgg16bn-Unet, achieves 99.4% overall accuracy and 98.2% Intersection over Union(IoU), while the most balanced network, mobilev3-Deeplabv3+, attains 98.9% accuracy and96.5% IoU, with a 27.59 fps(using an NVIDIA GeForce MX150 GPU) suitable for real-time UAV flights.

关键词： CNN Machine Vision Solar Inspection UAV Navigation Real-time and Embedded systems

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