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Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal Location Module 42

Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal...

引用

42nd Chinese control Conference, CCC 2023

作者： Xu, Dapeng Lu, Xiaobo Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

Fall events have unique dynamic features, which are not fully utilized by existing fall detection methods. Based on video understanding, we propose Fall-LSTM to learn such features pertinently without additional inputs. Fall-LSTM is composed of CNN-LSTM framework and two excitation modules i.e., Spatial Attention Module (SAM) and Temporal Location Module (TLM). SAM provides spatial constraints on motion for feature layers through foreground extraction and spatial pooling. TLM emphasizes frames with high probability of fall events to LSTM by inferring the rate and trend of motion in clips. Experimental results show that our proposed modules significantly improve the performance of LSTM model, outperforming the state-of-the-art methods on two public Fall Detection Datasets i.e., Le2i and UR. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Location

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Unknown-frequency harmonic disturbance estimation based speed regulation for single-frame control moment gyroscope

Unknown-frequency harmonic disturbance estimation based spee...

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2020 Jiangsu Annual Conference on automation, JACA 2020

作者： Yu, Yuxuan Yang, Jun Li, Shihua School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Jiangsu Nanjing210096 China

ISBN: (纸本)9781839535635

In the single frame control moment gyroscope (CMG) servo system, the permanent magnet synchronous motor (PMSM) is used to drive the frame. However, CMG is always affected by the multi-source strong coupling disturbance, and the disturbance form is mostly harmonic, so it is very important to accurately estimate the harmonic disturbance. In this paper, an estimation method of harmonic disturbance with unknown frequency and amplitude is proposed, and then the disturbance estimation is compensated by feedforward. The simulation results show the feasibility and performance of the proposed control method © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Permanent magnets

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Collision-free and Effecient Robotic Grasping based on Hierarchical Reinforcement Learning

Collision-free and Effecient Robotic Grasping based on Hiera...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Li, Yi Fang, Fang Liu, Chenyang Wang, Yutao Fan, Tao School of Automation Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

In the realm of robotics, grasping within unstructured environments has consistently been a challenging task. Direct grasping often results in failures due to collisions, and some pre-grasping maneuvers can eliminate the tightly stacked state between objects, thereby enhancing the success rate of grasping. In this paper, we opt for pushing as a pre-grasping maneuver. We propose a deep Q-network with a fused convolutional feature enhancement module to improve action value estimation, enhancing the robot’s pushing and grasping abilities. Additionally, a hierarchical reinforcement learning framework optimizes action sequences for better synergy between pushing and grasping. In simulated experiments, the model achieved a high grasp success rate with just a few hours of training, outperforming other methods in the literature. © The Institution of engineering & Technology 2024.

关键词： Adversarial machine learning

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Finite-time attitude stabilization for a rigid spacecraft using homogeneous method

Finite-time attitude stabilization for a rigid spacecraft us...

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作者： Du, Haibo Li, Shihua School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

ISBN: (纸本)9783902661937

This paper investigates the finite-time attitude stabilization problem for a rigid spacecraft with an unknown inertia matrix. By using homogeneous approach, a local continuous finite-time controller is first designed such that the attitude can be stabilized to the equilibrium in finite time. Then, to solve global attitude stabilization problem, a modified finite-time controller is proposed. Rigorous proof shows that the attitude can be stabilized to the equilibrium in finite time. Finally, a simulation example is given to demonstrate the efficiency of the proposed method. © 2011 IFAC.

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Evaluation of Smart Energy System Based on Machine Learning 10

Evaluation of Smart Energy System Based on Machine Learning

引用

10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Cheng, Xuran Chai, Lin School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering and School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781665424233

In the context of the gradual shortage of fossil energy and serious pollution, the voice of energy transformation is increasing year by year. With the development of Internet and artificial intelligence, the smart energy is getting more and more attention, and it is also the key direction of the upgrading of the world energy industry. In this process, in order to better understand its development and effectively guide the future construction and development of smart energy, appropriate and reasonable evaluation is essential. In the past few years, some researchers have put forward some evaluation methods for smart energy systems, and have achieved some good results. However, only traditional evaluation methods are used which are more subjective. Therefore, the application of machine learning method in the evaluation of smart energy system is worth trying and studying. Starting from the requirements of energy system and human development, this paper first introduces the emergence and development of smart energy and its evaluation methods. Simultaneously indicating the necessity of evaluation. Then the formation of the evaluation index system is briefly introduced. Secondly, machine learning algorithm models such as support vector machines, decision trees, and BP neural networks used are introduced respectively. Finally, experiments are carried out to train the model, and then comparing and analyzing the results. The final results show that the machine learning method plays a good role in the research of smart energy system evaluation, which is worthy of further research. © 2021 IEEE.

关键词： Decision trees

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Modified internal model control of PMSM speed-regulation system

Modified internal model control of PMSM speed-regulation sys...

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作者： Gu, Hao Li, Shihua School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

ISBN: (纸本)9783902661937

In this paper, the speed-regulation problem for permanent magnet synchronous motor (PMSM) system under vector control framework is studied. For the speed loop, a standard internal model controller is first designed based on a first-order model of PMSM by analyzing the relationship between reference quadrature axis current and speed. Considering the disadvantages that the standard IMC method is sensitive to control input saturation and provides a poor load disturbance rejection performance, a modified IMC is introduced where a feedback control term is added to form a composite control structure. For the two current-loops, PI algorithms are employed respectively. Simulation and experimental results show the effectiveness of the proposed control method. © 2011 IFAC.

关键词： Disturbance rejection

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Smoky Vehicle Detection Based on Improved Vision Transformer 21

Smoky Vehicle Detection Based on Improved Vision Transformer

引用

5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Yuan, Li Tong, Shuzhen Lu, Xiaobo School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781450389853

The harmful exhaust emissions of fuel vehicles in theworld are damaging to human health and the environment, thus detecting smoky vehicles from real road environment is significant. At present, methods of smoky vehicle detection based on deep learning have the problem of high false-positive rate. To improve the performance, a two-stage video smoky vehicle detection algorithm based on the smoke classification in the core region from detected vehicle object boxes is proposed in this paper. Specifically, the vehicle object detection is realized by the algorithm based on YOLOv3. The smoke classification is realized by combining Vision Transformer and distillation, and the loss function is optimized in the training process. Experimental results on our smoky vehicle dataset have shown that the improved model achieves an F1 score over 0.4, precision over 0.4, recall nearly 0.1 improvement compared with the basic model, which can effectively reduce the false-positive rate during detection.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Smoke

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Implicit Representation for Interacting Hands Reconstruction from Monocular Color Images 12th

Implicit Representation for Interacting Hands Reconstructio...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Zuo, Binghui Zhao, Zimeng Xie, Wei Wang, Yangang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9783031463044

Reconstructing interacting hands from monocular color images plays an important role in promoting the understanding of human behavior and the application of existing AR/VR technology. With the emergence of interacting hands datasets, numerous data-driven methods attempt to regress the MANO parameters of the left and right hand from the network. This formulation not only limits the handedness and the number of hands in the image but also introduces the deficiencies of the MANO into the interacting-hand reconstruction task. To address this obstacle, we present a novel framework for representing the surface of interacting hands with implicit functions. Our key idea is to construct an implicit neural occupancy network, which implicitly reconstructs interacting hands with image features as query strategies and conditions. The proposed query strategies only require one sample to obtain enough points on the surface. Our unified framework efficiently completes the task of reconstructing hands with the unlimited number, handedness, and interaction compactness from monocular color images. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Color

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A distributed finite-time economic dispatch algorithm in smart grid

A distributed finite-time economic dispatch algorithm in sma...

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2022 Jiangsu Annual Conference on automation, JACA 2022

作者： Lin, Luxin Wang, Xiangyu School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

ISBN: (纸本)9781839538476

This paper focuses on the design of an initialization-free distributed finite-time algorithm for the economic dispatch problem in smart grid, where the generation units only communicate with its neighbors to minimize the total cost cooperatively. Firstly, the optimal solution of the economic dispatch problem is analyzed in accordance with the saddle-point dynamics. Then, an initialization-free finite-time algorithm is presented to guarantee the active power generation and the incremental cost converge to the optimal solution in a distributed manner. At last, some numerical simulations are preformed to validate the proposed method. Copyright© JACA 2022 All rights reserved.

关键词： Smart power grids

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Distilling Siamese Trackers with Attention Mask 41

Distilling Siamese Trackers with Attention Mask

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第41届中国控制会议

作者： Han Sun Yongqiang Bai Wenbo Zhang State Key Lab of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,the introduction of Siamese network has brought new vitality to the object tracking ***,high-performance Siamese trackers cannot run at a real-time speed on mobile devices due to their complex and huge *** distillation is a common and effective model compression method,but it is difficult to be applied to the challenging task like object *** find out the fundamental cause is that the imbalance between the foreground and background in the object tracking task,which aggravates the problem of insufficient feature extraction ability of small ***,we propose the attention mask distillation(AMD) to help the student tracker focus on the foreground area faster and more *** attention mask can be easily obtained from the feature maps and brings fine-granularity to the traditional binary *** experimental results on OTB100 and VOT2018 show that our method enables the student tracker perform as well as the teacher *** the same time,it's able to run on the CPU at a hyper-real-time of 66 fps and achieves nearly 9 times model compression *** low computational and storage costs make it possible to deploy high-performance trackers on resource-constrained platforms.

关键词： Object Tracking Siamese Network Knowledge Distillation Attention Mask

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