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检索条件"任意字段=10th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2021"

共 359 条记录，以下是181-190 订阅

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Saturated Adaptive Pinning control and Consensus of Discontinuous Multi-Agent systems 10

Saturated Adaptive Pinning Control and Consensus of Disconti...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Wang, Jiafeng Ding, Dong Zhang, Jiancheng Tang, Ze School of Internet of Things Engineering Jiangnan University Wuxi214122 China School of Science Jiangnan University Wuxi214122 China

ISBN: (纸本)9781665424233

this paper studies the consensus problem for a kind of multi-agent systems with nonlinear and discontinuous dynamics through distributed adaptive control. By applying saturation strategy, the control signal is limited into a reasonable range in order to simulate the practical applications. then utilize the Gaussian error function and the differential mean value theorem to simulate the saturation effect. By designing the adaptive updating law, appropriate control gain is finally obtained. According to Filippov differential inclusion and measure selection theorem as well as Lyapunov stability theorem, sufficient conditions for achieving the consensus of multi-agent systems are derived. Ultimately, the validity of our conclusion is verified by establishing a numerical simulation. © 2021 ieee.

关键词： Multi agent systems

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Model Predictive control based on FSP-ADT Switching Sequence Constraint 10

Model Predictive Control based on FSP-ADT Switching Sequence...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Tang, Bin Song, Yang Qin, Ying School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Shanghai Key Laboratory of Power Station Automation Technology Shanghai200444 China

ISBN: (纸本)9781665424233

In this paper, we study the contractive set and model predictive control (MPC) problems for discrete-time switched linear systems, where the switching signals are under the constraint of fixed starting point average dwell time (FSP-ADT). the calculation method for terminal contractive set which is regarded as the terminal constrained set of the MPC problem is given. In addition, the algorithms and properties of all truncated FSP-ADT switching sequences in the predictive time domain are provided. From the perspective of the stability of the closed-loop switched system, what the terminal cost function should satisfy with regard to performance index are presented. Finally, the feasibility and the effectiveness of the proposed calculation method is proved by reliable numerical simulations. © 2021 ieee.

关键词： Model predictive control

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Auto-Detection of Tibial Plateau Angle in Canine Radiographs Using a Deep learning Approach 10

Auto-Detection of Tibial Plateau Angle in Canine Radiographs...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Tonima, Masuda Akter Hossain, F M Anim Dehart, Austin Zhang, Youmin Gina Cody School of Engineering Concordia University MontrealQC Canada Innotech Medical Industries Corp. VancouverBC Canada

ISBN: (纸本)9781665424233

Stifle joint issues are a major cause of lameness in dogs and it can be a significant marker for various forms of diseases or injuries. A known Tibial Plateau Angle (TPA) helps in the reduction of the diagnosis time of the cause. With the state of the art object detection algorithm YOLO, and its variants, this paper delves into identifying joints, their centroids and other regions of interest to draw multiple line axes and finally calculating the TPA. the methods investigated predict successfully the TPA within the normal range for 80 percent of the images. © 2021 ieee.

关键词： Object detection

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Adaptive Parameter Estimation for Nonlinear systems with Relaxed PE Condition 10

Adaptive Parameter Estimation for Nonlinear Systems with Rel...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： He, Haoran Na, Jing Huang, Yingbo Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China

ISBN: (纸本)9781665424233

this paper presents a novel adaptive parameter identification method based on an augmented regression for linearly parameterized nonlinear systems, which relaxes the persistence excitation (PE) condition. By setting filter operations, an augmented system is constructed. then, the augmented system is fused to decouple the estimated parameters. Furthermore, an adaptive estimator based on the parameter estimation error is designed to guarantee that the parameters exponentially converge to the true values. In this parameter estimation framework, not only the required PE condition can be relaxed but also the parameter estimation performance can be improved. Finally, comparative simulation results are provided to illustrate the effectiveness of the proposed method. © 2021 ieee.

关键词： Nonlinear systems

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A Visualized Quality Grading Method for Multi-index Products 10

A Visualized Quality Grading Method for Multi-index Products

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Wang, Peiming Wang, Zhaojing Yang, Weidong Wang, Yanwei Zheng, Ying School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Mechanical Electrical Engineering Wuhan Institute of Technology Hubei Wuhan430073 China

ISBN: (纸本)9781665424233

A graphical system for quality assessment is highly demanded in current manufacturing industry. It is typically difficult to grade products by multi-index quality data according to specification limits, especially when there is a complex correlation between indexes. this work introduces a visualized quality grading framework to solve the problems, which includes adopting Yoe-Johnson transformation and kernel principal component analysis to augment the insufficient quality data with correlations, and then visualizing the data through a modified 3D Kiviat diagram. the confidence region of each quality grade is determined respectively on the diagram to evaluate online products. the proposed methodology is tested on a semiconductor manufacturing and the result demonstrates its effectiveness and reliability. © 2021 ieee.

关键词： data visualization

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the Research of Aero-engine Digital Twin Model Based on Model-driven and data-driven Fusion Method∗∗National Science and Technology Major Project (2017-I-0003-0003) 10

The Research of Aero-engine Digital Twin Model Based on Mode...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Liu, Kui Wang, Pan Li, Qing Tsinghua University Department of Automation Beijing100084 China Aero-Engine Academy of China Beijing101304 China

ISBN: (纸本)9781665424233

With the rapid development of multi-field physical modeling, sensor network, big data processing and analysis and other information technologies, digital twin technology is gradually applied in the field of complex equipment operation and maintenance. Aero-engine is a typical complex equipment. the accurate monitoring in operation and performance degradation assessment and prediction are the key problems in maintenance. According to the definition of digital, the paper puts forward the concept of aero-engine digital twin and constructs an aero-engine digital twin model based on precise physical models, historical data and sensors data. the aero-engine digital twin model can predict the physical properties and can be applied to accurate monitoring in operation and performance degradation assessment and prediction. © 2021 ieee.

关键词： Sensor networks

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Dark web traffic detection method based on deep learning 10

Dark web traffic detection method based on deep learning

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Ma, Haoyu Cao, Jianqiu Mi, Bo Huang, Darong Liu, Yang Zhang, Zhenyuan College of Information Science and Engineering Chongqing Jiaotong University Chongqing400074 China

ISBN: (纸本)9781665424233

Network traffic detection is closely related to network security, and it is also a hot research topic now. With the development of encryption technology, traffic detection has become more and more difficult, and many crimes have occurred on the dark web, so how to detect dark web traffic is the subject of this study. In this paper, we proposed a dark web traffic(Tor traffic) detection scheme based on deep learning and conducted experiments on public data sets. By analyzing the results of the experiment, our detection precision rate reached 95.47%. © 2021 ieee.

关键词： Network security

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Cooperative Formation for Multiple Mobile Robots Based on data-driven Iterative learning control 10

Cooperative Formation for Multiple Mobile Robots Based on Da...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： You, Dongya Bu, Xuhui Hou, Rui Geng, Jiahao Yan, Kanghua School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454000 China

ISBN: (纸本)9781665424233

this paper presents a double closed-loop iterative learning control (ILC) strategy for the formation problem of wheeled mobile robots (WMRs). A formation algorithm based on distributed iterative learning is designed by introducing the leader-follower formation mode and the directed graph into the outer loop algorithm. Considering that the traditional robot control algorithm relies on the precise vehicle dynamics model, a velocity tracking algorithm based on data is proposed. the dynamic linearization method is used to transform dynamics into the data model based on the system input and output. In the inner loop algorithm, a finite-time velocity tracking algorithm for iterative domain updates is analyzed and designed according to the data model. the theoretical analysis of the convergence for position error and velocity tracking error is given, and the effectiveness of the double-closed loop formation strategy is verified by simulation. © 2021 ieee.

关键词： Mobile robots

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Grasping Detection Based on YOLOv3 Algorithm 10

Grasping Detection Based on YOLOv3 Algorithm

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Li, Zhiyuan Liu, Shan Polytechnic Institute Zhejiang University Hangzhou310015 China College of Control Science and Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665424233

In order to achieve multi-object grasping detection, this paper draws on the YOLOv3 algorithm, which has good performance in the field of object detection, and designs a grasping detection model based on deep learning. this model can recognize and locate multi-object in real time, and can predict the grasping point and the grasping deflection angle at the same time, which can realize end-to-end object positioning and grasping detection. For the specific application scenario, the corresponding dataset is automatically produced through data enhancement, which greatly saves the cost and time of manual collection and labeling. In the actual scene, we identify and locate the object and estimate the grasping point and grasping deflection angle of the object at the same time. 99.5% of the objects can be detected on the self-made data set. this method can greatly improve the accuracy of grasping detection in a specific scene. © 2021 ieee.

关键词： Object detection

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Repetitive control of Two-mass systems based on the Singular Perturbation Technique and Periodical Disturbance Observer 10

Repetitive Control of Two-mass Systems based on the Singular...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Zheng, Dong-Dong Li, Weixing Ren, Xuemei School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781665424233

In this paper, a repetitive learning control strategy for two-mass systems is proposed based on the singular perturbation technique (SPT) and a periodical disturbance observer (PDOB). Firstly, the original higher order system is decomposed into two lower order subsystems using the SPT. then PDOBs are designed for each subsystem, and sliding mode controllers are designed using the estimation results to achieve exponential convergence. Compared to other methods where the controller is designed based on the high order system model, the developed control method combines the SPT and PDOB together, thus the controller design problem is simplified and the control accuracy is improved because the periodic nature of the system is exploited. Furthermore, to reduce the oscillation at the beginning of each period when the PDOB is employed, a new repetitive learning law is developed, where an additional parameter is introduced to adjust the damping effect during the disturbance observation. the stability of the PDOB and the closed-loop system is analyzed via the Lyapunov approach and the effectiveness of the proposed PDOB and controller is verified by simulations. © 2021 ieee.

关键词： Closed loop systems

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