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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71-80 订阅

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Event-Triggered Adaptive controller Design with Reduced-Order Observer for Constrained Nonlinear systems 10

Event-Triggered Adaptive Controller Design with Reduced-Orde...

引用

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

作者： Wang, Lijie Liu, Yang Li, Hongyi Institute of Complexity Science Qingdao University Qingdao266071 China Automation Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9781665424233

this paper addresses the adaptive tracking control problem for a class of strict feedback nonlinear systems subject to input saturation and output constraint. By utilizing the designed event-triggering mechanism, the control input signals of the system are sampled aperiodically, which can reduce the number of transmissions as possible. Meanwhile, the closed-loop performance is still preserved. In addition, taking the input saturation error as the input of the constructed auxiliary system, a number of auxiliary signals are generated to deal with the effect of asymmetric input saturation. Note that partial state in the considered system is unavailable, then a more simple reduced-order observer is introduced to estimate them. Finally, simulation results on a one-link manipulator system are presented to demonstrate the feasibility of the proposed control scheme. © 2021 ieee.

关键词： Nonlinear systems

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Relaxed Nonquadratic Stabilization of Discrete-Time Takagi-Sugeno systems via An Efficient Switching Law 10

Relaxed Nonquadratic Stabilization of Discrete-Time Takagi-S...

引用

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

作者： Lu, Hongyu Gong, Aimin Xie, Xiangpeng College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9781665424233

this paper investigates the study on further enhancing the stabilization of discrete-time Takagi-Sugeno(T-S) systems by proposing a new fuzzy switching controller. Compared with the recent result reported in the literature, the proposed fuzzy switching controller is with a richer architecture on normalized fuzzy weighting functions(NFWFs) and a much more efficient switching law is developed for on-line activating the best pair of control gain matrices at each sampling instant. As a result, a larger system controllable interval can be obtained and it means that the conservatism of the previous result can be further reduced. In the end, some numerical simulations are provided to verify the effectiveness of the method developed in this paper. Furthermore, the proposed fuzzy switching controller is illustrated to be capable of providing much better control performance than the recent one for the same controllable plant. © 2021 ieee.

关键词： Fuzzy control

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Denoising control of Temperature Tracking for LiBr-H2O Absorption Refrigeration System 10

Denoising Control of Temperature Tracking for LiBr-H2O Absor...

引用

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

作者： Dong, Na Chang, Jianfang Lv, Wenjin Zhu, Shuo School of Electrical and Information Engineering Tianjin University Tianjin300072 China

ISBN: (纸本)9781665424233

To alleviate the noise in the temperature tracking of the LiBr-H2O absorption refrigeration system, denoising model-free adaptive control algorithm has been proposed in this paper. Firstly, the improved tracking differentiator is mainly used to alleviate the phase delay. Secondly, the model-free adaptive control with single input and single output has been extended to dual input and single output, equipped with the improved tracking differentiator, the denoising control of temperature tracking for LiBr-H2O absorption refrigeration system has been constructed. thirdly, the stability of denoising model-free adaptive control algorithm has been proven. Finally, the proposed algorithm is applied to the mathematical model and actual system, the experimental results prove the rapidity and immunity of the proposed algorithm in different systems. © 2021 ieee.

关键词： Absorption refrigeration

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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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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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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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Modeling of Aggregation Process Based on Feature Selection Extreme learning Machine of Atomic Search Algorithm 10

Modeling of Aggregation Process Based on Feature Selection E...

引用

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

作者： Wu, Chao Ren, Lihong Hao, Kuangrong College of Information Science and Technology Donghua University Shanghai201620 China

ISBN: (纸本)9781665424233

Polymerization process is a process in the production of polyester fiber, and its reaction parameter intrinsic viscosity has an important influence on the properties of the final polyester fiber. In this paper, a feature selection extreme learning machine model based on binary encoding Atom Search Optimization algorithm is proposed and applied to the polymerization process of polyester fiber production. Firstly, the distance measure of K-NearestNeighbor algorithm, combined with binary coding, and Atom Search Optimization algorithm are used to select features of industrial data to obtain the optimal data set. According to the data set, atom search optimization algorithm is used to optimize the weight and threshold of extreme learning machine and the activation function of the improved extreme learning machine. A prediction model with root mean square error as fitness function was established and applied to polyester production process. the simulation results show that the model has good prediction accuracy, which can be used for reference in the follow-up industrial production. © 2021 ieee.

关键词： Atoms

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Servo DC Motor Fault Diagnosis driven by Multi-source Heterogeneous data 10

Servo DC Motor Fault Diagnosis Driven by Multi-source Hetero...

引用

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

作者： Qiu, Demin Sun, Mingwei Fan, Haitao Shao, Junfei Lin, Yuanzhen Huo, Zengyuan Zhu, Jingle 63756 Unit of Pla Qingdao266110 China Nankai University Tianjin300110 China

ISBN: (纸本)9781665424233

According to the requirement of the on-line fault diagnosis of the servo DC motors used in TTC antenna, which is applicated in aerospace exploration, noise reduction and power spectrum analysis with wavelet packet are studied in this paper. the ability of feature extraction and pattern recognition are the characteristics of wavelet packet noise reduction, which are applied to analyze the motor's current signals in different branches, thus the characteristic parameters of the fault motors can be shown clearly. We proposed a servo DC motor fault diagnosis model based on informatization theory, which improves the reliability of fault diagnosis result, and the accuracy of data screening increases from 70.5% to 92%. the result shows that the fault diagnosis model can trigger alarm accurately, it is also effective and superior in fault location. © 2021 ieee.

关键词： Informatization

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Adaptive Iterative learning control for Non-equal Length Tasks in the Presence of Initial Errors 10

Adaptive Iterative Learning Control for Non-equal Length Tas...

引用

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

作者： Sun, Mingxuan Zou, Shengxiang Zhan, Yizhao He, Xiongxiong College of Information Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9781665424233

Both non-equal trail lengths and initial condition problems are practical challenges to learning control of robotic and mechatronic systems. Iterative learning to update input is still desired, because of the repetitive motion nature of the controlled objects. this paper concerns with the adaptive iterative learning control method for performing the non-identical tracking tasks, where the time scaling technique is used to normalize the non-equal trial lengths, while the error-tracking approach is adopted for coping with initial errors. theoretical results for the performance analysis are presented in detail. the uniform convergence of the tracking error is examined, while the boundedness of the variables in the closed-loop is characterized. the proposed control design method does not require the magnitude transformation, and removes the assumption of identical initial conditions. the time scaling technique is effective for assuring the expected tracking performance for the non-equal-length tasks in the presence of initial errors. © 2021 ieee.

关键词： learning algorithms

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