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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Cheng, Ting Liu, Shuai Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Control Science and Engineering Shandong University Jinan250061 China

ISBN: (纸本)9798350315196

Close and efficient cooperation between devices in the Industrial Internet of Things (IIoT) requires precise clock synchronization as a prerequisite. The uncertainty of IIoT networks and the complexity of industrial environments have led to less precise clock synchronization achieved by traditional algorithms and higher network resource consumption. This paper proposes a digital-twin-based clock synchronization scheme for IIoT systems. By building the digital model for each local clock to predict their clock skew, the information interaction required to achieve synchronization is reduced. In order to model the clock accurately, this paper proposes to use the extended state Kalman filter to handle uncertain dynamics and unknown measurement bias to improve the estimation accuracy of clock skew further. The simulation results show that the proposed algorithm can achieve high- precision clock synchronization while reducing the consumption of network resources. © 2023 IEEE.

关键词： Internet of things

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Multi-agent Deep Reinforcement Learning Based Multi-objective Charging control for Electric Vehicle Charging Station 7th

Multi-agent Deep Reinforcement Learning Based Multi-objectiv...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Magnetic Microrobots Fabricated by Photopolymerization and Assembly

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Cyborg and Bionic systems 2023年第1期4卷 41-46页

作者： Xiyue Liang Yue Zhao Dan Liu Yan Deng Tatsuo Arai Masaru Kojima Xiaoming Liu Key Laboratory of Biomimetic Robots and Systems Ministry of EducationState Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing Advanced Innovation Center for Intelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 182-8585Japan Department of Materials Engineering Science Osaka UniversityOsaka 560-8531Japan

Magnetic soft microrobots have great potential to access narrow spaces and conduct multiple tasks in the biomedical *** now,drug delivery,microsurgery,disease diagnosis,and dredging the blocked blood vessel have been realized by magnetic soft microrobots in vivo or in ***,as the tasks become more and more complex,more functional units have been embedded in the body of the developed magnetic *** magnetic soft microrobots with complex designed geometries,mechanisms,and magnetic orientation are now greatly challenging the fabrication of the magnetic *** this paper,we propose a new method combining photopolymerization and assembly for the fabrication of magnetic soft *** the micro-hand assembly system,magnetic modules with different shapes and materials are firstly arrayed with precise position and orientation ***,the developed photopolymerization system is employed to fix and link these modules with soft *** on the proposed fabrication method,3 kinds of soft magnetic microrobots were fabricated,and the fundamental locomotion was *** believe that the presented fabrication strategy could help accelerate the clinical application of magnetic microrobots.

关键词： Magnetic system precise

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Improvement of the Electrical Properties of Silicone Rubber Doped with Nano-zirconia Grafted by Voltage Stabilizer 4

Improvement of the Electrical Properties of Silicone Rubber ...

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4th IEEE International Conference on Electrical Materials and Power Equipment, ICEMPE 2023

作者： Zhu, Xiaoqian Zhou, Yuanxiang Zhang, Yunxiao Chen, Ming Liu, Xuanhao Tsinghua University State Key Lab of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Beijing China Fuzhou University College of Electrical Engineering and Automation Fuzhou China Xiamen Power Supply Company State Grid Fujian Electric Power Company Xiamen China Xinjiang University The Wind Solar Storage Division State Key Laboratory of Control and Simulation of Power System and Generation Equipment School of Electrical Engineering Urumqi China

ISBN: (纸本)9798350334678

Enhancing the electrical performance of silicone rubber (SiR) for cable accessories is noteworthy as they are almost the weakest parts of the cable system. Two types of voltage stabilizers were grafted onto the surface of nano-zirconia (ZrO2) particles, and the grafted nanoparticles were added to the SiR. Measurements such as breakdown strength, and conductivity were carried out to evaluate the electrical performance of SiR nanocomposites. The electrical performance measurement results indicated that the breakdown strength of the nanocomposite SiR improved while the conductance current was reduced. The trap distribution showed that the improvement of the electrical performance of the nanocomposite SiR is mainly due to the decrease of the shallow trap density or the increase of the deep trap density. © 2023 IEEE.

关键词： Nanoparticles

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Adversarially Robust Reinforcement Learning for Urban Traffic Signal control 5

Adversarially Robust Reinforcement Learning for Urban Traffi...

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5th IEEE International Conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Hamzah, Muhammad Shafly Joelianto, Endra Sutarto, Herman Yoseph Putri, Adiyana Institut Teknologi Bandung Instrumentation and Control Master Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia PT. Pusat Riset Energi Department of Intelligent System Bandung Indonesia Institut Teknologi Bandung Doctoral Program of Engineering Physics Bandung Indonesia

ISBN: (纸本)9798350364743

Urban traffic congestion presents critical challenges, resulting in delays, environmental pollution, and significant economic costs. While traditional traffic control methods, such as fixed-time and adaptive systems, have been widely implemented, they often fail in unpredictable conditions, particularly when confronted with noisy or inaccurate data. This research proposes a robust reinforcement learning (RL) solution for traffic signal control using the RADIAL-DQN (Robust Adversarial Loss DQN) algorithm. Integrating adversarial training enhances the system's robustness to real-world uncertainties. Evaluations conducted using a SUMO traffic simulation show that the robust agent produced an increase of only 60.71% in queue length under a projected gradient descent (PGD) adversarial attack, outperforming standard RL agents, which experienced an 89% increase. These results demonstrate the potential of robust RL to improve both the reliability and scalability of urban traffic control systems. © 2024 IEEE.

关键词： Traffic signals

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Integrating Blockchain Technology in a Cyber Physical system to Secure Data

Integrating Blockchain Technology in a Cyber Physical System...

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International Conference on control systems and Computer Science (CSCS)

作者： Balaban Bèatrix-May Sacală Ioan Ştefan Petrescu-Niţă Alina-Claudia Niţă Răzvan Department of System Engineering Faculty of Automatic Control and Computers Politehnica University of Bucharest Romania

Considering the constant growth and evolution of technology, being able to secure data is a challenge. This is why researchers find this a top research topic. Cyber-Physical systems are complex, large-scale systems that can be found in domains like healthcare, transportation, industrial controls systems or smart grids. Having many components that interact with each other, we can observe here the challenge in maintaining a secure environment for the data as data tampering or data extraction can occur, for example, in the actual transportation of data from one device to another. The main focus of this paper is to give an answer if blockchain technology provides a solution in building a secure network. We give a short review of the related work regarding blockchain integration in large-scale systems like Cyber-Physical systems. It was also briefly analyzed the layered structure of a blockchain and discussed some solutions for each layer. We then discussed about consensus algorithms for validation and authentication process. In general, consensus algorithms are implemented to assure the validation process of the nodes in a network. In this paper we tried to analyze and propose a model that offers an extra layer of security by adding the authentication step. In this way, the nodes that are validated are also considered trusted nodes in the network.

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Transfer Learning Based Multi-Perception Safety Strategy for Human-Robot Collaboration

Transfer Learning Based Multi-Perception Safety Strategy for...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Wei, Chongyi Wang, Changcong Bai, Shaoping Li, Yibin Tian, Xincheng Zhou, Lelai Shandong University Center for Robotics School of Control Science and Engineering Jinan250061 China Ministry of Education Engineering Research Center of Intelligent Unmanned System Jinan250061 China Aalborg University Department of Materials and Production Aalborg9220 Denmark

ISBN: (纸本)9798350327182

Human-robot collaboration (HRC) is vital to adapt to the significant change in manufacturers' demands for automation, and safety is a primary and major challenge that must be addressed for it. In this paper, a muti-perception safety strategy and framework are introduced to ensure human safety while trying to avoid reducing the work efficiency of the robot by taking human activity intentions and human-robot distance into account. To realize the safety strategy, an LSTM-CNN based neural network is built for human activity classification. To improve the generalization ability and performance of the network with data scarcity for existing deep learning-based human activity recognition methods, transfer learning-enabled activity recognition is proposed. Based on the studies, a feasible security system is implemented in the human-robot collaboration scenario. © 2023 IEEE.

关键词： Long short-term memory

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Simulation of Arc Erosion on the Main Contact of On-Load Tap Changer 4th

Simulation of Arc Erosion on the Main Contact of On-Load Tap...

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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Zhou, Yuanxiang Dai, Yasong Chen, Jianning Li, Yuhang Hou, Xuzhao Zhang, Zhen State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China The Wind Solar Storage Division of State Key Laboratory of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi830047 China

ISBN: (纸本)9789819974047

Long-term operation and switching of transformer on-load tap-changers can cause degradation and deterioration of the main contact material, even leading to contact arcing damage in severe cases. However, the arcing mechanism of the main contact during the switching has not been clarified yet. A magneto-hydrodynamic simulation method of main contact arcing has been proposed. The geometry of the main contact in transformer oil is simplified, and the simulation model of the arc temperature field of the main contact in transformer oil coupled with electric, magnetic, thermal and fluid fields is proposed. The dynamic evolution of the arc temperature has been investigated at peak currents of 2100 A, 1500 A, 600 A and 300 A, respectively. The results show that with the increase of the spacing between contacts, the temperature at arc core rises rapidly and then decreases slowly, and the temperature can reach 50177 K at 2100A. Due to the electron bombardment at the anode surface, the temperature at anode surface is higher than that at cathode surface under different chopped currents. The highest temperatures at anode and cathode surface can reach 4142.5 K and 4081.7 K respectively. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Deterioration

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A Strategy for Aerial Vehicle Trajectory Tracking using Robust Model Predictive control 23

A Strategy for Aerial Vehicle Trajectory Tracking using Robu...

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23rd International Conference on control systems and Computer Science Technologies, CSCS 2021

作者： Radulescu, Iulia Stefanoiu, Dan University Politehnica of Bucharest Department of Automatic Control and System Engineering Bucharest Romania

ISBN: (纸本)9781665439398

The objective of this paper is trajectory tracking for an aerial vehicle in presence of wind disturbances. The approach first involves linearizing the non-linear model of the aerial vehicle around operating points chosen along the trajectory to be followed. Then, a proposed modified version of robust min-max model predictive control is employed by using only one linearized model along the prediction horizon. The trajectory is generated using the concept of differential flatness. The simulation results of the proposed approach show that the aerial vehicle effectively manages to follow the trajectory under wind disturbances. © 2021 IEEE.

关键词： Trajectories

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Reconstruction of Temporal Envelope using 1D FLCNN-LSTM Speech Enhancement model 12

Reconstruction of Temporal Envelope using 1D FLCNN-LSTM Spee...

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12th IEEE International Conference on Advanced Computing, ICoAC 2023

作者： Anitha, M.R. Vijayalakshmi, B. Bhuvaneswari, N.S. B. S. Abdur Rahman Crescent Inst of Science and Technology Department of Ece Chennai India Ieee Madras Section Control System Society Chair Gkm College of Engineering and Technology Department of Eee Chennai India

ISBN: (纸本)9798350318210

The primary objective of speech enhancement algorithm is to enhance speech perception characteristics that have been damaged by background noise. Ensuring speech quality and intelligibility is essential in speech processing analysis for effective communication. To do this, a new temporal modulation processing speech enhancement approach is developed that reconstructs the temporal envelopes (TEVs) in the time frequency (T-F) domain using a one-dimensional feature learning convolutional neural network and long short-term memory (ID FLCNN-LSTM). This deep learning architecture is used to restore distorted envelopes. This approach is tested by utilising 2,700 words from nine different speech samples combined with babble noise and SSN (speech spectrum shaped random noise) at various SNRs. The proposed algorithm's performance is assessed using the Short time objective intelligibility (STOI) and Perceptual evaluation of speech quality (PESQ) metrics. The suggested model improved STOI and PESQ scores as 0. S2 and 2. S0 respectively. The experimental outcomes predicted for quality and intelligibility scores outperforms TEV algorithm, 1D-CNN, and other existing models in speech enhancement under noisy conditions. © 2023 IEEE.

关键词： Speech enhancement

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