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Adaptive Consensus Quantized control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1574-1589页

作者： Guoqiang Zhu Haoqi Li Xiuyu Zhang Chenliang Wang Chun-Yi Su Jiangping Hu the School of Automation Engineering Northeast Electric Power UniversityJilin 132012 the Jilin Province International Research Center of Precision Drive and Intelligent Control Jilin 132012China the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China the Department of Mechanical and Industrial Engineering Concordia UniversityQCMontrealH3B 1R6Canada the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China(

For a class of high-order nonlinear multi-agent systems with input hysteresis,an adaptive consensus output-feedback quantized control scheme with full state constraints is *** major properties of the proposed control scheme are:1)According to the different hysteresis input characteristics of each agent in the multi-agent system,a hysteresis quantization inverse compensator is designed to eliminate the influence of hysteresis characteristics on the system while ensuring that the quantized signal maintains the desired value.2)A barrier Lyapunov function is introduced for the first time in the hysteretic multi-agent *** constructing state constraint control strategy for the hysteretic multi-agent system,it ensures that all the states of the system are always maintained within a predetermined range.3)The designed adaptive consensus output-feedback quantization control scheme allows the hysteretic system to have unknown parameters and unknown disturbance,and ensures that the input signal transmitted between agents is the quantization value,and the introduced quantizer is implemented under the condition that only its sector bound property is *** stability analysis has proved that all signals of the closed-loop are semi-globally uniformly *** Star Sim hardware-in-the-loop simulation certificates the effectiveness of the proposed adaptive quantized control scheme.

关键词： Adaptive quantized control barrier Lyapunov function input hysteresis multi-agent systems

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Simulation of non-inductive vector control of permanent magnet synchronous motor based on sliding mode observer 3

Simulation of non-inductive vector control of permanent magn...

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3rd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Zhang, Caiyue Liu, Zipin Xu, Bowen Guilin University of Electronic Technology School of Electronic Engineering and Automation Guilin China Xi'An University of Science and Technology School of Electrical and Control Engineering Shaanxi Xi'an China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350398410

Permanent magnet synchronous motors (PMSM) are widely used due to their numerous benefits. It is critical to get rotor position and speed information in order to operate the motor accurately. Sensorless control techniques have emerged as a popular study area both at home and overseas. The sliding mode observer (SMO) may indirectly detect rotor position and has the benefits of easy implementation and efficient algorithms. In this study, a mathematical model for sensorless control of a PMSM is developed using SMO, vector control, and other techniques. With a surface-mounted PMSM as the study object, a mathematical model for sensorless control of PMSM is developed. PMSM's sliding mode observer model is built in the matlab/simulink environment. Experiments demonstrate that the system can track the rotor position and speed of the motor precisely and fulfill the requirements of sensorless vector control of PMSM. © 2023 IEEE.

关键词： Sensorless control

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Multi-User Cooperative Receive Scheme for Air-to-Ground Vortex Wave Communications

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China Communications 2025年第3期22卷 76-85页

作者： Zhang Beibei Chen Ruirui Lin Jinyang Li Qi Liang Liping Sun Yanjing School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Jiangsu Automation Research Institute Lianyungang 222061China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China

Orbital angular momentum(OAM)can achieve multifold increase of spectrum efficiency,but the hollow divergence characteristic and Line-of-Sight(LoS)path requirement impose the crucial challenges for vortex wave *** air-to-ground vortex wave communications,where there exists the LoS path,this paper proposes a multi-user cooperative receive(MUCR)scheme to break through the communication distance limitation caused by the characteristic of vortex wave hollow *** particular,we derive the optimal radial position corresponding to the maximum intensity,which is used to adjust the waist *** on the waist radius and energy ring,the cooperative ground users having the minimum angular square difference are ***,the signal compensation scheme is proposed to decompose OAM signals in air-to-ground vortex wave *** results are presented to verify the superiority of our proposed MUCR scheme.

关键词： air-to-ground capacity cooperative receive multi-user vortex wave communications

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Distributed Adaptive Formation control of Connected Vehicles with Actuator Saturation and Time-Varying Spacing 13

Distributed Adaptive Formation Control of Connected Vehicles...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Ji, Honghai La, Xiaoyan Fan, Lingling Wang, Li Liu, Shida Ren, Ye 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 study investigates the problem of distributed adaptive formation control of connected vehicles with actuator saturation and time-varying spacing. Firstly, optimization performance metrics are defined based on the requirements of vehicle formation control to ensure communication coordination among the following vehicles while enabling them to track the leader vehicle's trajectory. Secondly, time-varying spacing is introduced to meet the formation requirements in different scenarios. Furthermore, actuator saturation are imposed to ensure passenger comfort during the ride. Finally, the effectiveness of the proposed algorithm is validated through three numerical simulation cases. © 2024 IEEE.

关键词： Adaptive control systems

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Multi-Feature Fusion Transformer for Natural Language Inference 5

Multi-Feature Fusion Transformer for Natural Language Infere...

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5th International Conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2023

作者： Sun, Lei Li, Xiangyang Yan, Hengxin School of Electrical Engineering and Automation Tianjin University of Technology Tianj in Key Laboratory for Control Theory and Complicated Industry Systems Tianjin China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350357950

Natural Language Inference (NLI) is a branch of Natural Language Processing (NLP) whose main task is to determine the relationship between two sentences. Such tasks essentially use pre-trained models to ensure accuracy, and many applications are found in human-computer dialog and question-answering systems. However, in some cases where small devices are deployed offline, lightweight model implementations are often required to save computational resources. To address this problem and ensure more efficient inference capabilities, this paper describes how to improve the preexisting Transformer and proposes a Multi-Feature Fusion Transformer Network for NLI processing. The model integrates sequence features and introduces a priori information to enhance local features. It also achieves a comprehensive fusion of sequence information, local features, and non-local features, thus compensating for many potential shortcomings of Transformer. At the same time, it maintains the lightweight feature of the model and facilitates the implementation of downstream tasks. We verified the above point by experiments, our model has better inference performance compared to previous models used for the same task. The accuracy in the SNLI dataset reached 89.0%, while the matched and mismatched versions of MultiNLI reached 79.3% and 78.7%. © 2023 IEEE.

关键词： Feature Fusion Natural language inference Natural language processing Transformer

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An Early Multi-Fault Diagnosis Method of Lithium-ion Battery Based on Data-Driven 41

An Early Multi-Fault Diagnosis Method of Lithium-ion Battery...

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第41届中国控制会议

作者： Xin Gu Yunlong Shang Chijun Li Yuhao Zhu Bin Duan Jinglun Li Wenyuan Zhao School of Control Science and Engineering Shandong University School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Lithium-ion power battery is the "heart" of electric *** is significant to diagnose the battery fault quickly and accurately.A real-time data driven diagnosis approach for early battery faults based on improved principal component analysis is proposed in this *** technique rotates the battery pack voltage sequence into a new coordinate space through linear combination,while the detection metrics of square prediction errors and modified contribution plots are employed to achieve minor fault *** addition,the training sample of this method relies on the voltage sequence of the battery health state instead of the battery fault data which is difficult to *** experimental results demonstrate that this approach can not only locate the battery cell where the fault occurs,but also diagnose the open-circuit and short-circuit faults of the battery as well as the occurrence and duration of the fault in ***,the feasibility and robustness of the proposed method are verified by applying different experimental *** summary,the presented approach provides an easy-to-implement option that does not require accurate mathematical modeling,expert understanding,and complex computational processes.

关键词： Early fault diagnosis Lithium-ion battery pack Principal component analysis Data driven

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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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Simulated Ising Annealing Algorithm with Gaussian Augmented Hamiltonian Monte Carlo 42

Simulated Ising Annealing Algorithm with Gaussian Augmented ...

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42nd Chinese control Conference, CCC 2023

作者： Li, Langyu Wang, Hao Xie, Zhixin Liu, Zixuan Cui, Wei Pan, Yu Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China School of Mechanical Engineering and Automation Harbin Institude of Technology Shenzhen518055 China

ISBN: (纸本)9789887581543

A numerical technique called Simulated Ising Annealing (SIA) uses digital computers to obtain approximations of the ground states of Ising models. The quadratic unconstrained binary optimization (QUBO) problem in combinatorial optimization, which is challenging to solve through exhaustive search, has significant linkages to the Ising model. Therefore, SIA's main objective is to identify a better solution in finite iterations. In order to enhance the performance of the simulated annealing procedure, we adopt a Gaussian augmented Hamiltonian Monte Carlo (GAHMC) method in this study. We contrasted our algorithm with Gibbs sampling and local quantum annealing method. Finally, we discuss its application on QUBO problem. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Simulated annealing

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Image Recognition of Chinese Herbal Medicine Using Adaptive Gamma Correction Based on Convolutional Neural Network 13

Image Recognition of Chinese Herbal Medicine Using Adaptive ...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Ji, Honghai Liu, Xinjing Wang, Li Fan, Lingling Liu, Shida 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

Chinese herbal medicine (CHM) has gained significant attention due to its potential in treating various diseases. CHM image classification is crucial in fields such as smart medical care and medical teaching. However, accurately classifying CHM images has been a challenging task due to their fine-grained variability. To achieve automatic identification and classification of Chinese herbal medicines, we designed a method that combines image processing and deep learning. We established a dataset of CHM images, which includes 10 kinds of common Chinese herbal medicines, with 15,719 images in total. The dataset covers medicinal materials in various natural backgrounds and provides ample samples for training deep learning models. Regarding image processing, we proposed a method based on adaptive gamma correction(AGC) and compared it with CLAHE(Contrast Limited Adaptive Histogram Equalization)and traditional gamma correction(TGC) methods. Subsequently, we employed three pre-training models of convolutional neural networks based on transfer learning, namely GoogLeNet, ResNet-18, and MobileNetV2, to identify CHM images. The results of the verification indicate that the AGC-CNN model outperforms the CLAHE-CNN and TGC-CNN models in terms of classification accuracy and image quality improvement. © 2024 IEEE.

关键词： Contrastive Learning

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Sampled-Data Output Voltage Practical Tracking for Uninterruptible Power Supply Systems with Transmission Delays

Sampled-Data Output Voltage Practical Tracking for Uninterru...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Jia, Mengqi Liu, Wei Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798331504755

This paper aims at addressing output voltage practi-cal tracking problem for uninterruptible power supply systems by devising an aperiodic sampled-data control scheme. We consider the presence of transmission delay in the input channel. We demonstrate that the problem can be solved by a predictor-based sampled-data dynamic output feedback control law. Moreover, the tracking error can converge to a prescribed neighborhood of the origin. © 2024 IEEE.

关键词： Delay control systems

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