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Chinese automation Congress (CAC)

作者： Yaokun Hou Song Zheng Zhezhuang Xu Meng Yuan Ping Huang Weibing Huang Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Education College of Electrical Engineering and Automation Fuzhou University Fuzhou China Evomotion Co. Ltd. Shenzhen Guangdong China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The powerful representational and sequential modeling capabilities of Transformer have been validated in various fields such as natural language processing. However, how to better address sequential decision-making problems like robotic grasping through the Transformer architecture and achieve autonomous control of robotic grasping remains a longstanding challenge. Models that directly output continuous decision actions for robotic arms often rely on mean squared error (MSE) loss for training, which is unable to effectively handle the randomness and diversity of actions. This limitation leads to the generation of relatively singular actions in certain grasping scenarios, reducing the success rate of grasping. To address this issue, this paper proposes a Transformer-based method for discretizing robotic arm actions, where actions are discretized by dimension to enable autoregressive modeling. Experimental results demonstrate that this method effectively improves the grasping performance of robotic arms in simulation environments.

关键词： Training automation Decision making Grasping Transformers Manipulators Natural language processing Trajectory

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Dynamic model of tissue electroporation on the basis of biological dispersion and Joule heating

arXiv

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arXiv 2023年

作者： Guedert, R. Andrade, D.L.L.S. Silva, J.R. Pintarelli, G.B. Suzuki, D.O.H. Institute of Biomedical Engineering Federal University of Santa Catarina SC Florianópolis Brazil Department of Control Automation and Computer Engineering Federal University of Santa Catarina SC Blumenau Brazil

Electroporation is a complex, iterative, and nonlinear phenomenon that is often studied by numerical simulations. In recent years, tissue electroporation simulations have been performed using static models. However, the results of a static model simulation are restricted to a fixed protocol signature of the pulsed electric field. This paper describes a novel dynamic model of tissue electroporation that also includes tissue dispersion and temperature to allow time-domain simulations. We implemented the biological dispersion of potato tubers and thermal analysis in a commercial finite element method software. A cell electroporation model was adapted to account for the increase in tissue conductivity. The model yielded twelve parameters, divided into three dynamic states of electroporation. Thermal analysis describes the dependence of tissue conductivity on temperature. The model parameters were evaluated using experiments with vegetal tissue (Solanum tuberosum) under electrochemotherapy protocols. The proposed model can accurately predict the conductivity of tissue under electroporation from 10 kV/m to 100 kV/m. A negligible thermal effect was observed at 100 kV/m, with a 0.89 ◦C increase. We believe that the proposed model is suitable for describing the electroporation current on a tissue scale and also for providing a hint on the effects on the cell membrane. © 2023, CC BY-NC-SA.

关键词： Iterative methods

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Design of a Flexible Robot Arm for Safe Aerial Physical Interaction

Design of a Flexible Robot Arm for Safe Aerial Physical Inte...

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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Julien Mellet Andrea Berra Achilleas Santi Seisa Viswa Sankaranarayanan Udayanga G.W.K.N. Gamage Miguel Ángel Trujillo Soto Guillermo Heredia George Nikolakopoulos Vincenzo Lippiello Fabio Ruggiero Department of Electrical Engineering and Information Technology PRISMA Lab University of Naples Federico II Naples Italy CATEC Advanced Center for Aerospace Technologies Seville Spain Department of Computer Robotics and AI Team Electrical and Space Engineering LuleåUIniversity of Technology Luleå Sweden Department of Electrical Engineering and Photonics Automation and Control Group Technical University of Denmark Denmark Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

This paper introduces a novel compliant mechanism combining lightweight and energy dissipation for aerial physical interaction. Weighting 400 g at take-off, the mechanism is actuated in the forward body direction, enabling precise position control for force interaction and various other aerial manipulation tasks. The robotic arm, structured as a closed-loop kinematic chain, employs two deported servomotors. Each joint is actuated with a single tendon for active motion control in compression of the arm at the end-effector. Its elasto-mechanical design reduces weight and provides flexibility, allowing passive-compliant interactions without impacting the motors' integrity. Notably, the arm's damping can be adjusted based on the proposed inner frictional bulges. Experimental applications showcase the aerial system performance in both free-flight and physical interaction. The presented work may open safer applications for Micro Aerial Vehicle (MAV) in real environments subject to perturbations during interaction.

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Oscillation Suppression Method based on Power control Optimization of the Wind Farms 3

Oscillation Suppression Method based on Power Control Optimi...

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3rd IEEE International Power Electronics and Application Conference and Exposition, PEAC 2022

作者： Yang, Jiaqi Wang, Shaojun Li, Zhen Tian, Xu Liu, Bin Liu, Xiangdong Beijing Institute of Technology School of Automation Beijing China Co.Ltd Bayannur Power Supply Bureau Inner Mongolia China State Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing China Beijing University of Mining and Technology Beijing Electric Engineering and Automation Beijing China Tsinghua University Department of Electrical Engineering Beijing China

ISBN: (数字)9781665491419

ISBN: (纸本)9781665491419

Oscillation issues in the grid-connected wind farm system can severely deteriorate the power system security and lead to serious damage. Based on the impedance analysis method, many oscillation suppression methods have been proposed for reshaping the impedance characteristics of system to avoid the risk of oscillations. However, modifying converters' controllers to reshape the wind turbines (WTs) impedance and usage of additional damping devices for reshaping the grid impedance both are time-consuming and costly. Therefore, based on the sequence impedance model of the grid-connected wind farm system, this paper proposes a novel oscillation suppression method by optimizing the power control of wind farm. The system stability margin can be improved by modifying the number of online WTs and the output power of each WT to reshape the impedance of wind farm, under the precondition that the output power demand of wind farm is satisfied. Then, the intelligent particle swarm optimization (PSO) algorithm is used to solve the optimization approach to obtain the number of online WTs with optimal stability margin. Finally, the simulation confirms the effectiveness of the proposed oscillation suppression method. © 2022 IEEE.

关键词： System stability

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Modeling-free Learning control of Cross-coupled Fast Steering Mirror for 2-D Trajectory

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IFAC-PapersOnLine 2023年第2期56卷 5340-5345页

作者： Shingo Ito Ernst Csencsics Georg Schitter Department of Mechanical Engineering University of Fukui 3-9-1 Bunkyo Fukui 910-8507 Japan Automation and Control Institute (ACIN) TU Wien Vienna A-1040 Austria.

This paper proposes modeling-free inversion-based iterative control (MF-IIC) for a fast steering mirror, which is a dual-input dual-output system to generate 2-D optical scanning trajectories. To explicitly compensate for the cross-coupling motions, the MF-IIC iteratively updates the control inputs by learning from the previous trials based on a 2 × 2 Jacobian matrix. To operate the MF-IIC without system identification in advance, it estimates the Jacobian matrix including the non-diagonal elements for the cross-coupling dynamics simultaneously during learning. For experiments, 19 Hz and 20 Hz sine waves with an amplitude of 0.65° are used for a Lissajous pattern as a reference trajectory. Experimental results show that a tracking error of 320 × 10 − 3 degrees when feedback control is used for stability. By additionally combing the proposed MF-IIC, the error is decreased by a factor of 68 to 4.64 × 10 − 3 degrees. It is smaller than MF-IIC without considering the cross coupling explicitly, which achieves a tracking error of 12.1 × 10 - 3 deg. These two MF-IIC algorithms are also compared by the resulting sampled trajectories in the spatial domain. For that purpose, maximum dead zone diameter is defined as a diameter of the largest circle without sampled points in a scanning area in this paper. While the MF-IIC without considering the cross coupling explicitly for comparison creates a Lissajous pattern with a maximum dead zone diameter of 74.8 × 10 − 3 degrees, the proposed MF-IIC achieves a Lissajous pattern with a smaller maximum dead zone diameter of 72.9 × 10 − 3 degrees, demonstrating its effectiveness for high-quality scanning trajectories.

关键词： Mechatronic systems Motion control systems Scanners Learning algorithms

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An Energy-Efficient Communication Protocol for Power-Constrained IoT Networks: A Deep Reinforcement Learning Approach

An Energy-Efficient Communication Protocol for Power-Constra...

引用

Wireless and Optical Technologies (GCWOT), 2020 Global Conference on

作者： Syed Asad Ullah Syed Muhammad Khalid Umair Ahmed Korai Anayat Ullah Department of Electronic Engineering Balochistan University of Information Technology Engineering and Management Sciences (BUITEMS) Quetta Pakistan Control Automotive and Robotics Lab National Centre of Robotics and Automation (NCRA) BUITEMS Quetta Pakistan Department of Telecommunication Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

Power-limited devices (or sensors) constrain the deployment of modern IoT networks, such as Next-Generation Industrial IoT (NG-IIoT). These networks are envisioned as the key enablers to facilitate connectivity to billions of devices for applications like smart industries, smart healthcare, etc. This paper presents an optimal up-link communication protocol for a power-limited unlicensed sensor operating among numerous licensed sensors communicating in a time division multiple access (TDMA)-based scheme. The transmission of the power-limited sensor is ensured by employing the non-orthogonal multiple access (NOMA) technique during the time slot of a licensed sensor. To ensure energy-efficient communication, we maximize the throughput of the power-limited sensor using a deep reinforcement learning (DRL) framework recognized as a combined experience replay deep deterministic policy gradient (CER-DDPG) algorithm. Our simulation results demonstrated that the CER-DDPG-based communication protocol outperforms the benchmark schemes, such as DDPG and stochastic algorithms, in terms of throughput.

关键词： Optical losses NOMA Protocols Simulation Reinforcement learning Throughput Energy efficiency

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Decentralized Parametric Stability Certificates for Grid-Forming Converter control

arXiv

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arXiv 2025年

作者： Häberle, Verena He, Xiuqiang Huang, Linbin Dörfler, Florian Low, Steven Automatic Control Laboratory ETH Zurich Zurich8092 Switzerland Department of Automation Tsinghua University Beijing100084 China College of Electrical Engineering Zhejiang University Hangzhou310027 China Department of Computing and Mathematical Sciences the Department of Electrical Engineering Caltech PasadenaCA91125 United States

We propose a decentralized framework for guaranteeing the small-signal stability of future power systems with grid-forming converters. Our approach leverages dynamic loop-shifting techniques to compensate for the lack of passivity in the network dynamics and establishes decentralized parametric stability certificates, depending on the local device-level controls and incorporating the effects of the network dynamics. By following practical tuning rules, we are able to ensure plug-and-play operation without centralized coordination. Unlike prior works, our approach accommodates coupled frequency and voltage dynamics, incorporates network dynamics, and does not rely on specific network configurations or operating points, offering a general and scalable solution for the integration of power-electronics-based devices into future power systems. We validate our theoretical stability results through numerical case studies in a high-fidelity simulation model. Copyright © 2025, The Authors. All rights reserved.

关键词： Decentralized control

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A Numerical Analysis of Pressure Characteristics in the Deflector Jet Pilot Stage Valve with an Innovative Deflector Deflection

SSRN

引用

SSRN 2024年

作者： Li, Songjing Saha, Bijan Krishna Shakib, Md. Shah Najmus Peng, Jinghui Jihan, Jahidul Islam Department of Fluid Control and Automation Harbin Institute of Technology Harbin150001 China Department of Mathematics Faculty of Science and Engineering University of Barishal Barishal8254 Bangladesh Harbin Institute of Technology China

Electric-hydraulic servo-valves are extensively used in the aerospace, mechanical, and aerodynamics industries to control missile wings or airplanes precisely. Aiming to reduce undesired flow phenomena inside the deflector jet pilot valve, innovative deflections of deflector are proposed in this paper. A numerical analysis is performed using STAR CCM+ to investigate the pressure and flow characteristics inside the pilot stage of deflector jet servo-valve. For observing the pressure, cavitation and flow characteristics, the Eulerian multi-phase model, VOF phase interaction, and realizable model for the turbulent flow are used during numerical simulations. The supply and outlet pressure are kept at 24 MPa and 1 MPa, respectively. To verify the calculated numerical results for turbulent flows, the velocity distribution to the V-groove exit of the deflector jet pilot stage is calculated and discussed with the theoretical results. The numerically calculated results show good agreement with published analytical results. The result shows that by the innovative rotation of the deflector both in clockwise and anti-clockwise directions, significant pressure in the receivers is obtained than traditionally moving deflector to the left and right for the same supply pressure. Moreover, when the deflector is positioned clockwise or anti-clockwise by 5 degrees, less cavitation is observed than in the traditional model. The key finding of this paper shows that innovative structural optimization of the amplifier disk and deflector is of utmost importance. © 2024, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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STGSA:A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 226-238页

作者： Zebing Wei Hongxia Zhao Zhishuai Li Xiaojie Bu Yuanyuan Chen Xiqiao Zhang Yisheng Lv Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the Shandong Key Laboratory of Smart Transportation(Preparation) Shandong Jiao Tong UniversityShanghai 200240China the College of Science China University of PetroleumQingdao 266580China the Department of Transportation Engineering School of Transportation Science and TechnologyHarbin Institute of TechnologyHarbin 150090China IEEE

The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the *** existing frameworks typically utilize separate modules for spatial and temporal correlations ***,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some ***,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between *** overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies ***,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution *** each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting ***,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven ***,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global *** projects the embedding input repeatedly with multiple different ***,the predicted values are generated by stacking several multi-stream *** experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA

关键词： Deep learning graph neural network(GNN) multistream spatial-temporal feature extraction temporal graph traffic prediction

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Assisted Physical Interaction: Autonomous Aerial Robots with Neural Network Detection, Navigation, and Safety Layers

arXiv

引用

arXiv 2024年

作者： Berra, Andrea Sankaranarayanan, Viswa Narayanan Seisa, Achilleas Santi Mellet, Julien Gamage, Udayanga G.W.K.N. Satpute, Sumeet Gajanan Ruggiero, Fabio Lippiello, Vincenzo Tolu, Silvia Fumagalli, Matteo Nikolakopoulos, George Soto, Miguel Ángel Trujillo Heredia, Guillermo CATEC Advanced Center for Aerospace Technologies Seville Spain Robotics and AI Team Department of Computer Electrical and Space Engineering LuleåUniversity of Technology Luleå Sweden PRISMA Lab Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy Automation and Control Group Department of Electrical Engineering and Photonics Technical University of Denmark Denmark Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

The paper introduces a novel framework for safe and autonomous aerial physical interaction in industrial settings. It comprises two main components: a neural network-based target detection system enhanced with edge computing for reduced onboard computational load, and a control barrier function (CBF)-based controller for safe and precise maneuvering. The target detection system is trained on a dataset under challenging visual conditions and evaluated for accuracy across various unseen data with changing lighting conditions. Depth features are utilized for target pose estimation, with the entire detection framework offloaded into low-latency edge computing. The CBF-based controller enables the UAV to converge safely to the target for precise contact. Simulated evaluations of both the controller and target detection are presented, alongside an analysis of real-world detection performance. © 2024, CC BY.

关键词： Unmanned aerial vehicles (UAV)

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