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Chinese control and Decision Conference, CCDC

作者： Peng Liu Hongliang Fang Jiang-Wen Xiao Yan-Wu Wang Xiao-Kang Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Ministry of Education Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Wuhan China

When a large number of distributed power and renewable energy are connected to the smart grid, the volatility and intermittency of renewable energy bring some challenges to the smart grid. Therefore, accurate medium-term load forecasting is essential because it is conducive to the stability of the power grid and can provide data support for the power generating plan. Many factors affect medium-term load forecasting and the real-time electricity price is a very important factor among them. In this paper, a multi-scale model based on LSTM model is proposed to extracts features from 3 different time scales including half-hourly time scale, daily time scale and monthly time scale. At first, the half-hourly data is processed by a half-hourly data processing layer to extract the half-hourly features. Then, its output is concatenated with the daily load data and is input into a daily data processing layer. Finally, the daily features are concatenated with the monthly load data and they are input into a monthly data processing layer to extract the monthly features and get the final forecasting results. The case study results demonstrate that the proposed multi-scale model has better performance than the single-scale models.

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RP-MSTC*: Multi-Agent Coverage Path Planning Algorithm Emphasizing Local Area Updates

RP-MSTC*: Multi-Agent Coverage Path Planning Algorithm Empha...

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Neuromorphic Computing (ICNC), International Conference on

作者： Yong Yang Dingxin He Huantao Mao Hong Chen Hongtao Wu Zhi-Wei Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

Compared to traditional area coverage algorithms, this paper proposes a re-plannable multi-agent coverage path planning algorithm to address issues such as low coverage rate of multiple agents in large-scale scenarios like warehouses and inability to cope with local environmental changes. Initially, the MSTC * algorithm is utilized to create the coverage path based on the available map information. To address scenarios like idle areas for material placement, the method introduces local area detection and path re-planning to enhance the coverage rate. This paper verifies the feasibility and effectiveness of the algorithm under different maps through simulation experiments. Compared with the coverage situation of other coverage path planning algorithms in environments with local area updates, the algorithm proposed in this paper has a higher coverage rate in this scenario.

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A New Multi-Scale Model for Medium-Term Load Forecasting

A New Multi-Scale Model for Medium-Term Load Forecasting

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第35届中国控制与决策会议

作者： Peng Liu Hongliang Fang Jiang-Wen Xiao Yan-Wu Wang Xiao-Kang Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education

When a large number of distributed power and renewable energy are connected to the smart grid,the volatility and intermittency of renewable energy bring some challenges to the smart ***,accurate medium-term load forecasting is essential because it is conducive to the stability of the power grid and can provide data support for the power generating *** factors affect medium-term load forecasting and the real-time electricity price is a very important factor among *** this paper,a multi-scale model based on LSTM model is proposed to extracts features from 3 different time scales including half-hourly time scale,daily time scale and monthly time *** first,the half-hourly data is processed by a half-hourly data processing layer to extract the half-hourly ***,its output is concatenated with the daily load data and is input into a daily data processing ***,the daily features are concatenated with the monthly load data and they are input into a monthly data processing layer to extract the monthly features and get the final forecasting *** case study results demonstrate that the proposed multi-scale model has better performance than the single-scale models.

关键词： Deep learning medium-term load forecasting LSTM real-time electricity price

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Fixed-time extended state observer-based trajectory tracking control for autonomous underwater vehicles

Fixed-time extended state observer-based trajectory tracking...

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作者： Zheng, Jiaqi Song, Lei Liu, Lingya Yu, Wenbin Zhu, Shanying Wang, Yiyin Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

In this paper, we investigate the trajectory tracking control problem for autonomous underwater vehicles (AUVs) with time-varying external disturbances of currents and waves in the sea. To solve the problem, a fixed-time extended state observer (FTESO)-based tracking controller is proposed. Firstly, by using the extended state observer, the FTESO is proposed for estimating the external disturbances and the velocities of the AUV within the fixed convergence time. Based on the FTESO, the fixed-time controller is proposed for reducing the tracking errors and improving robustness performance. Theoretical analysis is given, which shows that the unknown external disturbances can be compensated and tracking error can converge to zero within the fixed time. Simulation results show that the proposed FTESO controller not only guarantees the fixed-time convergence but also reduces the trajectory tracking errors of the AUV. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Autonomous underwater vehicles

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Laser tracking leader-follower automatic cooperative navigation system for UAVs

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International Journal of Agricultural and Biological Engineering 2022年第2期15卷 165-176页

作者： Rui Ming Zhiyan Zhou Zichen Lyu Xiwen Luo Le Zi Cancan Song Yu Zang Wei Liu Rui Jiang College of Engineering South China Agricultural University/Guangdong Laboratory for Lingnan Modern AgricultureGuangzhou 510642China College of Computer and Control Engineering Minjiang University/Fujian Provincial Key Laboratory of Information Processing and Intelligent ControlFuzhou 350108China Guangdong Provincial Key Laboratory for Agricultural Artificial Intelligence(GDKL-AAI) Guangzhou 510642China Guangdong Engineering Research Center for Agricultural Aviation Application(ERCAAA) Guangzhou 510642China Key Laboratory of Key Technology on Agricultural Machine and Equipment South China Agricultural UniversityMinistry of Education of P.R.ChinaGuangzhou 510642China

Currently,small payload and short endurance are the main problems of a single UAV in agricultural applications,especially in large-scale *** is one of the important methods to solve the above problems of UAVs by improving operation efficiency through multi-UAV cooperative *** study proposed a laser tracking leader-follower automatic cooperative navigation system for *** leader in the cluster fires a laser beam to irradiate the follower,and the follower performs a visual tracking flight according to the light spot at the relative position of the laser tracking *** on the existing kernel correlation filter(KCF)tracking algorithm,an improved KCF real-time spot tracking method was *** with the traditional KCF tracking algorithm,the recognition and tracking rate of the optimized algorithm was increased from 70%to 95%in indoor environment,and was increased from 20%to 90%in outdoor *** navigation control method was studied from two aspects:the distance coordinate transformation model based on micro-gyroscope and navigation control *** error of spot position was reduced from the maximum(3.12,−3.66)cm to(0.14,0.12)cm by correcting the deviation distance of the spot at different angles through a coordinate correction *** image coordinate conversion model was established for a complementary metal-oxide-semiconductor(CMOS)camera and laser receiving device at different mounting *** laser receiving device was divided into four regions,S0-S3,and the speed of the four regions is calculated using an uncontrollable discrete Kalman *** outdoor flight experiments of two UAVs were carried out outdoors using this *** experiment results show that the average flight error of the two UAVs on the X-axis is 5.2 cm,and the coefficient of variation is *** average flight error on the Z-axis is 7.3 cm,and the coefficient of variation is *** study demonstrated the possibility

关键词： two-UAVs cooperative visual navigation laser tracking

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Antifungal activity of curcumin-mediated photodynamic inactivation against Fusarium graminearum on maize

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Grain & Oil Science and Technology 2025年第1期8卷 21-31页

作者： Shuliang Dong Lu Chen Shaojie Li Konglong Feng Guang Liu Hao Dong Guizhi Xu Huajian Ou Yang Liu Yong Zhao Jingjing Wang Guangdong Provincial Key Laboratory of Intelligent Food Manufacturing Foshan UniversityFoshan 528225China College of Food Science and Technology Shanghai Ocean UniversityShanghai 201306China Shanghai Sixth People’s Hospital Affiliated to Shanghai JiaoTong University Shanghai 201306China Sericultural&Agri-Food Research Institute Guangdong Academy of Agricultural Sciences/Key Laboratory of Functional Foods Ministry of Agriculture and Rural Affairs/Guangdong Key Laboratory of Agricultural Products ProcessingGuangzhou 510610China College of Light Industry and Food Sciences Zhongkai University of Agriculture and EngineeringGuangzhou 510225China National Technical Center(Foshan)for Quality Control of Famous and Special Agricultural Products Foshan 528225China

The natural curcumin-mediated photodynamic inactivation(PDI)was developed,and its inactivation potency against Fusarium graminearum in vitro and in vivo was systematically investigated by fluorescence probe assay,trypan blue staining,scanning electron microscope(SEM),confocal laser scanning microscopy(CLSM),*** showed that under the irradiation of blue LED,the photosensitizer of curcumin was excited to generate massive reactive oxygen species(ROS)in the cells of ***,and the PDI completely inactivated their mycelia and spores under the treatment of 150μM curcumin and 10.8 J/cm^(2)*** analysis found that the PDI ruptured the cellular microstructures,damaged the cell membrane by increasing its permeability and oxidizing the lipids,degraded the intracellular DNA and proteins inside the spores of ***,the PDI also potently killed>99.99%spores of *** on maize under the treatment of 200μM curcumin and 10.8 J/cm^(2)***,the PDI suppressed the production of zearalenone(ZEN),and residual ZEN could not be detected after the storage of maize for 10 ***,this study systematically explored the inactivation efficiency of curcumin-mediated PDI against both the mycelia and spores of ***,which provides a valid and promising method to control the fungal hazards in grains.

关键词： Fusarium graminearum Photodynamic inactivation(PDI) Spores Mycelia Zearalenone(ZEN)

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A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB image

arXiv

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arXiv 2023年

作者： Jiang, Changlong Xiao, Yang Wu, Cunlin Zhang, Mingyang Zheng, Jinghong Cao, Zhiguo Zhou, Joey Tianyi Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Alibaba Group China Singapore Singapore

3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimation method-to RGB domain under interacting hand condition. Our key idea is to equip A2J with strong local-global aware ability to well capture interacting hands’ local fine details and global articulated clues among joints jointly. To this end, A2J is evolved under Transformer’s non-local encoding-decoding framework to build A2J-Transformer. It holds 3 main advantages over A2J. First, self-attention across local anchor points is built to make them global spatial context aware to better capture joints’ articulation clues for resisting occlusion. Secondly, each anchor point is regarded as learnable query with adaptive feature learning for facilitating pattern fitting capacity, instead of having the same local representation with the others. Last but not least, anchor point locates in 3D space instead of 2D as in A2J, to leverage 3D pose prediction. Experiments on challenging InterHand 2.6M demonstrate that, A2J-Transformer can achieve state-of-the-art model-free performance (3.38mm MPJPE advancement in 2-hand case) and can also be applied to depth domain with strong generalization. The code is avaliable at https://***/ChanglongJiangGit/A2J-Transformer. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Distributed Event-Triggered Observer-based control for Linear Networked Multi-Agent Systems

Distributed Event-Triggered Observer-based Control for Linea...

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European control Conference (ECC)

作者： Zhuo-Rui Pan Wei Ren Xi-Ming Sun Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper studies the distributed event-triggered observer-based control problem for linear multi-agent systems with heterogeneous dynamics and external disturbances. In particular, the multi-agent system and its observers communicate via multiple independent and asynchronous networks, the observers can communicate with each other, and each controller is designed via the corresponding observer. In such a framework, we first investigate the information transmission in the closed-loop system, then apply local information to develop distributed event-triggered mechanisms, and finally derive sufficient conditions for the co-design strategy to ensure the desired performance. Further discussions are presented to show the generality of the proposed framework. A numerical example from power systems is presented to illustrate the derived results.

关键词： Sufficient conditions Power system dynamics Europe Information processing Observers Closed loop systems Multi-agent systems

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A Lightweight Object Detection Network for Industrial Robot Based YOLOv5

A Lightweight Object Detection Network for Industrial Robot ...

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2023 china Automation Congress, CAC 2023

作者： Zhong, Tao Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

With the rapid development of deep learning, it has been widely applied in fields such as computer vision, natural language processing, and robotics. Despite the superior performance of deep learning in object detection, most industrial vision robots still rely on traditional object detection methods due to computational constraints of robot controllers. In order to improve the performance of object detection for vision robots, a lightweight 3D object detection network based on You Only Look Once version 5 (YOLOv5) is proposed for satisfying industrial production. YOLOv5 work to efficiently object detection using deep convolutional networks. In terms of model deployment, we adopt a novel OpenVINO-based model deployment approach. The OpenVINO framework significantly enhances the inference speed of models by model optimization and compression. Our model achieves a 70% reduction in inference time compared to the baseline model on CPU. The effectiveness of the proposed method is demonstrated through experiments. © 2023 IEEE.

关键词： Object detection

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UniAnimate: Taming Unified Video Diffusion Models for Consistent Human image Animation

arXiv

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arXiv 2024年

作者： Wang, Xiang Zhang, Shiwei Gao, Changxin Wang, Jiayu Zhou, Xiaoqiang Zhang, Yingya Yan, Luxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Alibaba Group Hangzhou310052 China University of Science and Technology of China Hefei230026 China

Recent diffusion-based human image animation techniques have demonstrated impressive success in synthesizing videos that faithfully follow a given reference identity and a sequence of desired movement poses. Despite this, there are still two limitations: i) an extra reference model is required to align the identity image with the main video branch, which significantly increases the optimization burden and model parameters;ii) the generated video is usually short in time (e.g., 24 frames), hampering practical applications. To address these shortcomings, we present a UniAnimate framework to enable efficient and long-term human video generation. First, to reduce the optimization difficulty and ensure temporal coherence, we map the reference image along with the posture guidance and noise video into a common feature space by incorporating a unified video diffusion model. Second, we propose a unified noise input that supports random noised input as well as first frame conditioned input, which enhances the ability to generate long-term video. Finally, to further efficiently handle long sequences, we explore an alternative temporal modeling architecture based on state space model to replace the original computation-consuming temporal Transformer. Extensive experimental results indicate that UniAnimate achieves superior synthesis results over existing state-of-the-art counterparts in both quantitative and qualitative evaluations. Notably, UniAnimate can even generate highly consistent one-minute videos by iteratively employing the first frame conditioning strategy. Code and models will be publicly available. Project page: https://***/. Copyright © 2024, The Authors. All rights reserved.

关键词： Animation

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