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Adaptive control for a class of discrete-time time-delay systems with regard to delay parameter

Journal of systems engineering and Electronics 2009年第1期20卷 159-167页

作者： Chai Lin Cheng Ming Fei Shumin Zhai Junyong Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast Univ. Nanjing 210096 P. R. China School of eleetrics Southeast Univ. Nanjing 210096 P. R. China

The memory state feedback control problem for a class of discrete-time systems with input delay and unknown state delay is addressed based on LMIs and Lyapunov-Krasovskii functional method. Under the action of our designed adaptive control law, the unknown time-delay parameter is included in memory state feedback controller. Using LMI technique, delay-dependent sufficient conditions for the existence of the feedback controller are obtained. Finally, the effectiveness of the proposed design method is demonstrated by a numerical example.

关键词： discrete-time time-delay systems adaptive control linear matrix inequality.

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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...

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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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Research on Temperature Error Calibration Method of Fluxgate Sensor 11th

Research on Temperature Error Calibration Method of Fluxga...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Yang, Ruiping Ge, Jian Luo, Wang Hu, Xiangyun She, Jinhua Chugo, Daisuke Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering Kwansai Gakuin University Osaka669-1330 Japan School of Geophysics and Geomatics China University of Geosciences Wuhan430074 China Hubei Subsurface Multi-scale Imaging Key Laboratory Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9789819647521

The fluxgate sensor is the most widely used sensor in vector magnetic measurement. However, during long-term continuous observation, the fluxgate sensor will produce large measurement errors due to changes in ambient temperature. This paper proposes a temperature calibration method for the fluxgate sensor based on polynomial fitting to address the temperature error of fluxgate sensors. First, the effect of temperature on the performance indicators of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature calibration model of the fluxgate sensor was constructed. And compared it with other temperature calibration method, the result shows that the proposed temperature calibration method is relatively simple and can better achieve real-time calibration for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were implemented. The temperature drift was reduced from about 700 nT before calibration to about 1 nT, root mean square error RMSE=11.7189, indicating that the proposed method has a good temperature calibration effect on the data measured by the fluxgate sensor within the variable temperature background. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Curve Fitting Fluxgate Sensor Temperature Calibration

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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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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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Anisotropy dependence of chip formation and plastic deformation in Fe-25Cr-20Ni austenitic stainless steel during micro-scratching

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Tribology International 2025年 210卷

作者： Lv, Beibei Chen, Qinglong Li, Yunjie Wang, Fangyuan Zhang, Yulong Han, Jie Jiang, Zhengyi Xia, Wenzhen Institute of Microstructure and Micro/Nanomechanics School of Metallurgical Engineering Anhui University of Technology Maanshan 243032 China State Key Laboratory of Digital Steel Northeastern University Liaoning Shenyang 110819 China State Key Laboratory of Powder Metallurgy Central South University Changsha 410083 China Research Institute of SD Steel Shandong Iron and Steel Co. Ltd. Shandong Jinan 271104 China School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong 2522 NSW Australia Anhui Engineering Research Center of Low-carbon Metallurgy and Process Control Anhui University of Technology Ma'anshan 243002 China State Key Laboratory for Turbulence and Complex Systems Peking University Beijing 100087 China

The wear characteristics of the tribological pair and the mechanisms of material removal are significantly influenced by the plastic deformation of the contact surface during the tribological process of metallic materials. Chip formation is recognized as one of the primary mechanisms contributing to material loss during the wear process. However, the underlying mechanisms governing chip formation remain incompletely elucidated. This paper employs micro-scratch testing to investigate the wear behavior of the {001}, {101}, and {111} grains in austenitic stainless steel under varying scratch directions and applied loads. The transition from initial indentation contact to plowing and subsequent chip formation is systematically examined, revealing the influence of crystallographic orientation and scratch direction on chip formation mechanisms. Our results demonstrate that the chip formation and plastic deformation exhibit substantial dependence on crystallographic orientation and scratch direction, which are closely associated with the activation of specific slip systems within the grains. The depth profile within the worn track and the surface topography surrounding it have a major impact on the frictional response and chip formation process. A critical depth for chip formation is identified under specific loading conditions, below which chip formation is more likely to occur. This research provides valuable insights into the micro-scale tribological behavior of face-centered cubic metallic materials, offering a theoretical foundation for optimizing material properties, enhancing wear resistance, and prolonging service life in engineering applications. © 2025 Elsevier Ltd

关键词： Anisotropic tribological property Chip formation Crystallographic orientation Micro-scratch Plastic deformation

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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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Smoky Vehicle Detection Based on Improved Vision Transformer 21

Smoky Vehicle Detection Based on Improved Vision Transformer

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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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