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检索条件"任意字段=8th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2019"

共 336 条记录，以下是1-10 订阅

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Proceedings of 2019 ieee 8th data driven control and learning systems conference, ddcls 2019

Proceedings of 2019 IEEE 8th Data Driven Control and Learnin...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

ISBN: (纸本)9781728114545

the proceedings contain 250 papers. the topics discussed include: dual attention message passing model for scene graph generation;feature extraction for controller design by deep auto-encoder neural network and least squares policy iteration;data driven control for a class of nonlinear SISO systems with uniform quantizer using encoding and decoding mechanism;content based image retrieval via sparse representation and feature fusion;active disturbance rejection control of ship course based on deep belief network;remaining useful life prediction of lithium-ion battery based on unscented kalman filter and back propagation neural network;and multiple fault diagnosis for sucker rod pumping systems based on matter element analysis with F-statistics.

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Iterative learning-Based data-driven control for Unknown Unmanned Marine Vehicles with Actuator Faults 12

Iterative Learning-Based Data-Driven Control for Unknown Unm...

引用

ieee 12th data driven control and learning systems conference (ddcls)

作者： Liu, Huiying Hao, Li-Ying Dalian Maritime Univ Coll Marine Elect Engn Dalian Peoples R China

ISBN: (纸本)9798350321050

this paper researches the iterative learning-based data-driven control for unknown unmanned marine vehicles with actuator faults, while considering the trajectory tracking problem in the presence of external disturbances. Using the partial form dynamic linearization technique, we establish an equivalent dynamic linearization data model with independent disturbance of unmanned marine vehicles. the disturbance and input data have different pseudo partial derivative matrices, which increases the immunity of the UMVs to disturbance in the environment. Additionally, we propose an equivalent data model with unknown pseudo partial derivative matrices that includes both actuator faults and UMV dynamics information. And, an iterative learning-based fault-tolerant trajectory tracking data-driven control scheme is developed such that the error of trajectory tracking is convergent under external disturbance and actuator faults. Finally, the examples are provided to validate the effectiveness of the proposed iterative learning trajectory tracking control scheme in this paper.

关键词： data-driven Iterative learning control Actuator Faults Trajectory Tracking Unmanned Marine Vehicles

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Robot Skill learning and Generalization based on Human-robot Collaboration and Computer Vision 13

Robot Skill Learning and Generalization based on Human-robot...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhang, Xin Zhang, Ruiqing Huang, Deqing Li, Yanan School of Electrical Engineering Southwest Jiaotong University Chengdu611756 China

ISBN: (纸本)9798350361674

the paper presents a novel approach for human-robot skill transferring. Firstly, we propose a method that combines dynamic time warping (DTW) with the Gaussian mixture model (GMM) to reconstruct the demonstrated skills, including reference path and pose, for each workpiece. Secondly, we integrate hand-eye coordination to facilitate dataset creation and employ YOLOv8 for model training. Finally, we utilize a neural network to obtain the current workpiece's category and pose information and then transform the previous skills into the current workpiece coordinate system. the effectiveness and robustness of our proposed method have been validated on a 7-DOF Sawyer robot equipped with a camera. © 2024 ieee.

关键词： Robot learning

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Observer-based data-driven Sliding Mode control for a Discrete-time Nonlinear Multiagent systems 12

Observer-based Data-driven Sliding Mode Control for a Discre...

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ieee 12th data driven control and learning systems conference (ddcls)

作者： Yin, Caiyun Lin, Guohuai Chen, Guangdeng Ma, Hui Li, Hongyi Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Guangdong Univ Technol Guangdong Prov Key Lab Intelligent Decis & Cooper Guangzhou 510006 Guangdong Peoples R China Guangdong Univ Technol Sch Math & Stat Guangzhou 510006 Peoples R China

ISBN: (纸本)9798350321050

In this work, an observer-based sliding mode control strategy is proposed for a discrete-time nonlinear multiagent systems (MASs) with unknown disturbance. Only some agents are capable of acquiring the reference trajectory, and the dynamic models of the agents are unknown. Unlike the traditional model-based consensus control protocol, this method is data-driven and solely dependent on the input/output (I/O) data of the agents. the stability of the proposed control strategy is ensured by theoretical analysis and the simulation outcomes ultimately validate the viability of the developed approach.

关键词： data-driven Multiagent systems Sliding mode control

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Adaptive learning control with Extended Bandwidth for Synchronization Motion Stages 12

Adaptive Learning Control with Extended Bandwidth for Synchr...

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ieee 12th data driven control and learning systems conference (ddcls)

作者： Sun, Pengyu Song, Fazhi Chen, Shuaiqi Liu, Yang Harbin Inst Technol Ctr Ultraprecis Optoelect Instrument Engn Harbin Peoples R China Harbin Inst Technol Minist Ind & Informat Technol Key Lab Ultraprecis Intelligent Instrumentat Harbin Peoples R China Harbin Inst Technol Sch Astronaut Harbin Peoples R China

ISBN: (纸本)9798350321050

this paper proposes a novel method to improve synchronization precision and reduce the influence of stochastic noises in lithography motion stages. Specifically, the multiple-channel adaption-learning-function synchronization iterative learning control (MASILC) method we give uses a multiple-channel approach based on A-type of ILC, with adaptive parameters to address the divergence situation caused by stochastic noises in different channels. We verify the superiority of the MASILC method and analyze its stability and convergence performance in theory. Furthermore, we introduce an effective adaptive method inspired by the stochastic acceleration optimization method. Simulation comparisons with analogous approaches demonstrate the effectiveness and superiority of the proposed method in various circumstances.

关键词： iterative learning control (ILC) lithography motion systems synchronization control multiple-channel method adaptive parameters

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Real-Time Modified Predictive control Model for Large Scale Wind Turbine Pitch System 13

Real-Time Modified Predictive Control Model for Large Scale ...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Lin, Qi-Wu Liu, Zhao-Hua School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (纸本)9798350361674

In order to effectively reduce the fluctuation of blade loads during independent pitch change of large wind turbines, a real-time correction model predictive control (MPC) control strategy for independent pitch control is proposed. the strategy adds a linear processor on the basis of the model predictive control, and by discretizing the pitch angle with multiple times and variable accelerations and sending them to the controller in sequence, it achieves the effect of real-time correction, reducing signal fluctuations and blade load fluctuations. the simulation results show that the proposed control strategy can effectively reduce the load fluctuation and has better performance than PI control and MPC control alone. © 2024 ieee.

关键词： Predictive control systems

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A License Plate Recognition Method Based on YOLOv8-Pose and E-LPRNet 13

A License Plate Recognition Method Based on YOLOv8-Pose and ...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Ji, Honghai Shi, Qirui Fan, Lingling Wang, Li Xiong, Shuangshuang School of Electronics & Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100096 China

ISBN: (纸本)9798350361674

this paper proposes a license plate recognition method based on YOLOv8-Pose and E-LPRNet for complex scenarios such as urban roadside and road inspection. E-LPRNet is a character recognition network formed by modifying the activation function of the backbone network in LPRNet (License Plate Recognition Network). this method also includes a license plate correction feature, which accurately recognizes license plate characters even when the plates are at large angles, thereby increasing the recognition accuracy. A series of experiments using a large license plate dataset verified the effectiveness of this method. © 2024 ieee.

关键词： Character recognition

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Robust fixed-time sliding mode control of underactuated Furuta pendulum system 12

Robust fixed-time sliding mode control of underactuated Furu...

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ieee 12th data driven control and learning systems conference (ddcls)

作者： Wang, Zhujun Zhou, Xinhao Zhang, Ancai Liang, Xiao Pan, Guangyuan Linyi Univ Sch Automat & Elect Engn Linyi 276005 Shandong Peoples R China Linyi Univ Key Lab Complex Syst & Intelligent Comp Univ Shan Linyi 276005 Shandong Peoples R China

ISBN: (纸本)9798350321050

A Furuta pendulum is a typical underactuated mechanical system with two degrees of freedom (DOF) and only one input. We address the robust stabilization control problem for this 2-DOF underactuated system with a matched external disturbance. A fixed-time sliding mode control method is presented. First, the dynamic motion model of the system is established using the Euler-Lagrange modeling method. And then, we get the approximate linearization model of the system around the origin equilibrium point and construct a homeomorphic coordinate transformation for this model. After that, a sliding mode surface and a fixed-time robust controller are designed for the transformed system. the developed controller ensures the system's state variables to reach the sliding mode surface in a fixed time. this guarantees the fixed-time robust stabilization control objective to be achieved. Finally, two numerical examples demonstrate the validity of our presented control strategy.

关键词： Furuta pendulum fixed-time stable sliding mode control robust stabilization

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A Novel YOLOv8-Pose-Based Algorithm for Abnormal Behavior Analysis of Quadruped Robots 13

A Novel YOLOv8-Pose-Based Algorithm for Abnormal Behavior An...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Liu, Shida Zhang, Tianzhen Ji, Honghai Wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100000 China

ISBN: (纸本)9798350361674

In this paper, a novel abnormal behavior analysis algorithm based on YOLOv8 is proposed for the target recognition problem of guide robot dog. the algorithm is based on the human posture estimation model of YOLOv8 for abnormal behavior analysis, and by extracting the coordinate information of the key points of the human body, it can make conditional decisions on abnormal behaviors such as falling forward, backward and sideways, so as to realize the real-time monitoring of the blind people and send out alarms in time. the proposed algorithm ensures the accuracy and speed of the recognition while not taking up a lot of computational resources of the computer. the proposed method is applied to a real quadruped robot platform, and the effectiveness and applicability of the proposed algorithm is verified through a large number of experiments, which in this paper are based on the actual data collected from different human posture pictures. © 2024 ieee.

关键词： Microrobots

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Improved Lightweight Vehicle and Pedestrian Target Detection Algorithm for YOLOv8 13

Improved Lightweight Vehicle and Pedestrian Target Detection...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Ji, Honghai Lu, Yue Fan, Lingling Liu, Shida Ren, Ye Wang, Li School of Electronics & Control Engineering North China University of Technology Beijing100144 China

ISBN: (纸本)9798350361674

In the context of road scenes, detecting targets poses challenges such as mutual occlusion, small sizes, and dense distributions, leading to difficulties in detection and target loss. To address these issues, a road scene target detection algorithm is proposed based on improvements to YOLOv8. Firstly, a lightweight VanillaNet is employed as the backbone feature extraction network. Secondly, an SENet module is introduced in the Feature Fusion Network (Neck) to enhance the model's learning ability in deep-level features, thereby addressing detection challenges caused by mutual occlusion of targets. Finally, the MPDIoU loss function is chosen to replace the original YOLOv8 loss function for model optimization. Experiments are conducted using images from the Pascal VOC dataset, specifically samples of Person, Car, Bus, Motorcycle, and Bicycle categories, for training and testing. the experimental results indicate that the improved algorithm exhibits a 3.5% increase in average precision compared to the original YOLOv8 algorithm, with notable improvements in target omission and false detection scenarios. © 2024 ieee.

关键词： Automobile testing

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