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11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Zhang, Hongwei Xiong, Wenbo Zhang, Weiwei Lu, Shuai School of Electronic and Information Xi'an Polytechnic University Xi'an710048 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China School of Medical Technology Beijing Institute of Technology Beijing100081 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Automatic defect detection is an essential and challenging problem in the yarn-dyed weaving production process, this paper proposed a novel U-shaped Swin Transformer auto-encoder reconstructed model for yarn-dyed shirt piece defect detection. This method uses the model of Transformer to extract the global features of the image better and reconstruct it more accurately, which solves the problems of scarce and unbalanced type of defect samples and high cost in actual production. Firstly, for a certain pattern, using defect-free samples adding Gaussian noise to train the reconstruction model. Then, the image to be tested is input into the Transformer model to obtain the corresponding output image. Subsequently, the residual image is calculated by subtracting the input image and its corresponding output image. Finally, the defect localization can be achieved through thresholding and morphological operation. The experiment result verifies the effectiveness of the proposed method on various types of yarn-dyed shirt pieces. © 2022 IEEE.

关键词： Yarn

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Fabrication and characterisation of La0.8Sr0.2CrO3-ITO thermocouples for high-temperature sensing

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International Journal of Nanomanufacturing 2022年第1期18卷 1-8页

作者： Chen, Bohan Huang, Manguo Zhang, Meiju Liang, Xiaobo Liu, Dan Wang, Lingyan Niu, Gang Zhang, Zhongkai Tian, Bian Shi, Peng Ren, Wei Electronic Materials Research Laboratory Key Laboratory of the Ministry of Education and International Center for Dielectric Research School of Electronic and Information Engineering Xi’an Jiaotong University Xi’an710049 China Beijing Changcheng Aeronautic Measurement and Control Technology Research Institute Beijing101111 China Aviation Key Laboratory of Science and Technology on Special Condition Monitoring Sensor Technology Beijing101111 China State Key Laboratory for Mechanical Manufacturing Systems Engineering School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China

La0.8Sr0.2CrO3-ITO thermocouples were successfully fabricated by screen printing. The La0.8Sr0.2CrO3 powder used for screen printing was obtained by the sol-gel method. The highest thermal voltage output was maintained at 270 mV at 1270°C. The microstructure of La0.8Sr0.2CrO3 and ITO electrode films were analysed by SEM. Thermoelectric response test was implemented to measure the performance of La0.8Sr0.2CrO3-ITO thermocouple by three times of thermal cycles. The results indicated that La0.8Sr0.2CrO3-ITO thermocouple showed good stability at high temperature. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Screen printing

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Optimized operation method for AC-DC hybrid microgrid considering Dynamic efficiency and Maximum absorption power of battery

Optimized operation method for AC-DC hybrid microgrid consid...

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2022 International Conference on Informatics, Networking and Computing, ICINC 2022

作者： Dong, Wei Zhang, Xiaolin Yao, Guangxiu Lei, Jiazhi Liu, Zhao China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems Beijing China Nanjing University of Science and Technology School of Automation Nanjing China

ISBN: (纸本)9798350309690

As an important part of AC-DC hybrid microgrid, battery energy storage systems (ESSs) can improve the flexibility and economy of system operation. This paper presented an optimized operation method for AC-DC hybrid microgrid considering the dynamic efficiency and maximum absorption power of vanadium redox flow battery (VRB). Firstly, the model of dynamic efficiency and maximum absorption power for VRB ESSs were respectively established. And then, the structure of AC-DC hybrid microgrid was designed and the operation optimization method of AC-DC hybrid microgrid was reasonably constructed. Finally, the proposed optimized operation method for AC-DC hybrid microgrid was solved by particle swarm optimization. Case studies showed that dynamic efficiency and maximum absorption power of VRB ESSs have a great influence on the operation of AC-DC hybrid microgrid. © 2022 IEEE.

关键词： Particle swarm optimization (PSO)

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A Deep Reinforcement Learning control Method for a Four-Link Brachiation Robot

A Deep Reinforcement Learning Control Method for a Four-Link...

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Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM), International Conference on

作者： Xuanyu Zhang Zishang Ji Haodong Zhang Rong Xiong School of Mechatronical Engineering Beijing Institute of Technology Beijing China State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China

Brachiation is a common way for primates to move between treetops. This movement has the characteristics of adapting to complex, discontinuous environment and low energy consumption. However, traditional control methods are often difficult to complete such tasks where the support is point-contact and discrete. Reinforcement learning (RL) gives a solution to such tasks due to its strong ability to adapt to complex environments. Therefore, in this paper, we design a four-link underactuated robot model with a pair of suspended hooks and propose a deep reinforcement learning-based control method to realize its brachiation between bars. The policy for outputting control signals is trained using the proximal policy optimization (PPO) algorithm because of its strong performance and ability to handle continuous action spaces. A reward function considering energy consumption and the challenges posed by the introduction of hooks is designed to obtain an energy-optimized control policy. Through simulation, a comparison is drawn against the author's previously proposed method of generating energy-optimal offline trajectories and tracking by model predictive control (MPC), thereby substantiating the superiority of the proposed method outlined in this paper.

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AUTOSIM:Automated Urban Traffic Operation Simulation via Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1871-1881页

作者： Yuanqi Qin Wen Hua Junchen Jin Jun Ge Xingyuan Dai Lingxi Li Xiao Wang Fei-Yue Wang Zhejiang Lab Hangzhou 310030China ECARX Technology Co. Ltd.Shanghai 201811China IEEE Zhejiang Supcon Information Company Ltd. Hangzhou 310052China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Indiana University-Purdue University Indianapolis(IUPUI) IndianapolisIndiana 46202 USA School of Artificial Intelligence Anhui UniversityHefei 230039China

Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic *** has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time *** cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry *** a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal ***,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a *** computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations.

关键词： Conditional generative adversarial network signalized urban networks short-term link speed prediction

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Event-Triggered Energy Optimization of Wireless Sensor Networks 19

Event-Triggered Energy Optimization of Wireless Sensor Netwo...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Liu, Lu Song, Ruizhuo Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665472432

Aiming at limited communication and energy re-sources in wireless sensor networks (WSN s), this paper proposes an energy management scheme of WSNs via adaptive dynamic programming (ADP) based on event-triggered mecha-nism (ETM). The optimal control strategy obtained by iteration can schedule the sensor nodes and make the nodes switch between working and sleeping situations, thus improving the energy utilization and extending the service life of the energy-constrained WSNs. Firstly, the mathematical model of WSNs is established, and the state is estimated by extended Kalman filter (EKF) algorithm to improve the measurement accuracy. Then, ADP solves the designed value function to achieve the scheduling plan. On the premise of system stability, ETM is applied to activate the controller on demand, which can reduce communication burden and save WSNs energy consumption. Finally, the simulation experiment reveals that the proposed algorithm can reduce the unnecessary triggering times of the controller effectively while ensuring the requirements, and avoid data congestion and interaction resource waste. © 2022 IEEE.

关键词： Energy utilization

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Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms

arXiv

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arXiv 2023年

作者： Soleymani, Mahdi Liu, Qiang Mahdavifar, Hessam Balzano, Laura Halıcıoglu Data Science Institute University of California San Diego United States The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm to tackle the problem in the binary field, due to Saunderson et al. [1]. In this paper, we improve upon the theoretical guarantees for the algorithm provided in [1]. Furthermore, we formulate a new graphical model for the matrix completion problem over the finite field of size q, Fq, and present a message passing (MP) based approach to solve this problem. The proposed algorithm is the first one for the considered matrix completion problem over finite fields of arbitrary size. Our proposed method has a significantly lower computational complexity, reducing it from O(n2r+3) in [1] down to O(n2) (where, the underlying matrix has dimension n × n and r denotes its rank), while also improving the performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

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A perspective on Attitude control Issues and Techniques

arXiv

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arXiv 2022年

作者： Zhang, Dandan Jin, Xin Su, Hongye The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

This paper reviews the attitude control problems for rigid-body systems, starting from the attitude representation for rigid body kinematics. Highly redundant rotation matrix defines the attitude orientation globally and uniquely by 9 parameters, which is the most fundamental one, without any singularities;minimum 3-parameter Euler angles or (modified) Rodrigues parameters define the attitude orientation neither globally nor uniquely, but the former exhibits kinematical singularity and Gimbal lock, while the latter two exhibit geometrical singularity;once-redundant axis-angle or unit quaternion globally define the attitude rotation but not uniquely using 4 parameters, but the former is not appropriate to define very small or very large rotations, while the latter shows unwinding phenomenon despite of the reduced computation burden. In addition, we explore the relationships among those attitude representations, including the connections among Gimbal lock, unwinding phenomenon and a nowhere dense set of zero Lebesgue measure. Based on attitude representations, we analyze different attitude control laws, almost global control and global attitude control, nominal and general robustness, as well as the technique *** Codes 70E50 Copyright © 2022, The Authors. All rights reserved.

关键词： Attitude control

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Model Predictive control for Nonlinear Bilateral Teleoperation systems With Time Delay 41

Model Predictive Control for Nonlinear Bilateral Teleoperati...

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第41届中国控制会议

作者： Yu Liu Chuanzhi Zang Yuqi Liu Peng Zeng School of Artificial Intelligence Shenyang University of Technology Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Bilateral teleoperation systems have received extensive attention as a substitute for the human to perform tasks in remote and hazardous *** paper proposes a model predictive control strategy for nonlinear bilateral teleoperation systems based on Long-Short Term Memory(LSTM) ***,model predictive control is used to achieve good tracking performance in the presence of input constraints in the *** the same time,considering the influence of different proficiency operators operating the master manipulator on the system performance,the error between the actual master manipulator trajectory and the reference trajectory is introduced into a linear feedback term to compensate for the decrease in system control accuracy caused by the error of ***,the LSTM network is used to predict the trajectory of the master manipulator in the future time equivalent to the network transmission *** predictions are used to control the remote slave manipulator,thereby eliminating the impact of communication delay on the ***,in slave sides,the trajectory creators are applied to generate the desired trajectories to achieve good force feedback *** experiments are carried out to verify the proposed control strategy,which can guarantee good performance with both position tracking and force feedback under time delay.

关键词： Model predictive control bilateral teleoperation long-short term memory network communication delay

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