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arXiv 2023年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with adversarial constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize network regret and cumulative constraint violation. A novel distributed online algorithm is proposed and it achieves an O(T max{c,1−c}) network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the number of rounds and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T 1−c). Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to O(log(T)), and the network cumulative constraint violation bound is reduced to O(√log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is the first to achieve reduced (network) cumulative constraint violation bounds for (distributed) online convex optimization with adversarial constraints under Slater’s condition. Finally, the theoretical results are verified through numerical simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Economic and social effects

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Analysis of Electro-mechanical Actuator Transmission Clearance under High-temperature Conditions 9

Analysis of Electro-mechanical Actuator Transmission Clearan...

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9th International Conference on Fluid Power and Mechatronics, FPM 2023

作者： Liu, Zhicheng Yu, Tian Hong, Rui Liu, Li Su, Hao Lin, Jionghui Jiang, Chaofan Shang, Yaoxing School of Automation Science and Electrical Engineering Beihang University Beijing China Technology on Aircraft Control Laboratory Beihang University Beijing China Research Institute for Frontier Science Beihang University Beijing China Tianmushan Laboratory Xixi Octagon City Yuhang District Hangzhou China Chengdu Aircraft Design and Research Institute Chengdu China Ningbo Institute of Technology Beihang University Ningbo China Key Laboratory of Advanced Aircraft Systems Beihang University Ministry of Industry and Information Technology China

ISBN: (纸本)9798350304947

More Electric Aircraft with electro-mechanical actuator(EMA) or electro-hydrostatic actuator(EHA) is the development trend of new aircraft. In high temperature conditions, the transmission clearance of EMA transmission system may change because of thermal deformation. If the transmission clearance decreases, the EMA may get stuck;If the transmission clearance increases, it will affect the control accuracy of the aircraft control. This paper investigates the transmission clearance of EMA transmission system when subjected to the combined effects of an external high-temperature environment and internal heat sources. To calculate the temperature distribution of EMA transmission system, A heat transfer model of the EMA is established. Based on this temperature distribution, the EMA transmission clearance can be calculated. an EMA dynamic model, involved nonlinear clearance, is established to analysis the effects of the transmission clearance on the actuator's output performance. This research provides a reference for studying the design clearances of EMA under high temperature conditions. © 2023 IEEE.

关键词： Electromechanical actuators

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IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using Wheel-Encoder and Inertial-RGB-Depth Measurements

IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using ...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Yuanhao Liu Wei Liang Chu Wang Xin Zhang Huanbing Gao Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences School of Information and Electrical Engineering Shandong Jianzhu University Shandong Key Laboratory of Intelligent Buildings Technology Jinan China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

Safe & smart move (SSM) aims to help industrial vehicular robot (IVR), such as warehousing robots, running safely and smartly by detecting the obstacles in front and maintaining a safe distance & attitude. However, the traditional SSM methods suffer the drawbacks of limited ranges, inaccurate regression of safety distance & orientation between the robot and the forward unexpected obstacles, and the inappropriate IVR control strategies. To solve these issues, this paper designs an innovative real-time safety-aware framework using the complementary Wheel-Encoder and Inertial-RGB-Depth measurements to ensure the IVR running safely, reasonably and reliably. To estimate the robot running states, we take advantages of the complementary wheel encoder, monocular RGB images and inertial measurements to obtain the robot positions, orientations, angular and linear velocities in a tightly-coupled manner. To improve the safety relative distance & attitude estimation accuracy, we exploit the RGB and depth measurements in a task-oriented fashion. The forward obstacles with the specific contours are detected using the Mask-RCNN model, followed by the Gaussian Mixture Model to obtain the forward obstacle depth. Eventually, an IVR control strategy is designed to maintain the robot safety distance and orientation, and to keep the minimum damage to the robot mechanical system. The presented method has been evaluated on the developed industrial vehicular robot safety perception platform. The experimental results prove the competitiveness against the state-of-the-art methods.

关键词： Service robots Warehousing Robot vision systems Wheels Reliability engineering Safety Mobile robots Mechanical systems Velocity measurement Gaussian mixture model

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Enhancing Electric Vehicle Efficiency and Stability With Fuzzy Logic control

Enhancing Electric Vehicle Efficiency and Stability With Fuz...

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Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET), International Conference on

作者： Younes Belhadjer Khaled Mouheb Billel Naceri Hamou Ait Abbas Kouider Laroussi Laboratory Of The Applied and Automation and Industrial Diagnostic University of Djelfa Djelfa Algeria Laboratory of Identification Commande Control and Communication (LI3CUB) University of Biskra Biskra Algeria Laboratory of Electrical and Automatic Systems Engineering (LGSEA) University Akli Mohand Oulhadj Bouira Algeria

ISBN: (数字)9798350346336

ISBN: (纸本)9798350346343

The current global oil crisis and growing environmental concerns are driving car manufacturers to prioritize research and development programs aimed at developing electric and hybrid vehicles. Maintaining vehicles mobile while minimizing environmental impact, and finding clean and efficient propulsion solutions is paramount. in this context the systemic control and energy management of electric vehicles presents a major challenge. To address this challenge, several scientists have proposed control strategies for the permanent magnet synchronous machine (PMSM) that is used in electric vehicles, which is the main focus of this contribution. The paper begins by examining the use of classical control strategies, such as the PI controller, and then explores the application of fuzzy logic to control the PMSM. The use of fuzzy logic allows for the consideration of parametric perturbations on the vehicle dynamics caused by factors such as slope and external environmental factors. This provides a more comprehensive and flexible approach to controlling the PMSM in electric vehicles. The paper concludes with a discussion of simulation results that provide insights into the effectiveness of these control strategies. Overall, this paper highlights the importance of optimal control and energy management in electric vehicles as a means of finding clean and efficient propulsion solutions in response to the oil crisis and growing ecological constraints.

关键词： Fuzzy logic System dynamics Oils Simulation Propulsion Regulation Stability analysis

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Air-ground cooperative exploration of 3D complex environment with maximized visibility and obstacles avoidance

Air-ground cooperative exploration of 3D complex environment...

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2021 International Conference on Unmanned Aircraft systems, ICUAS 2021

作者： Wu, YuXuan Wang, Jing Zhou, Meng Dong, Zhe Chen, YangQuan College of Information Science and Technology Beijing University of Chemical Technology Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China Mechatronics Embedded Systems and Automation Lab University of California MercedCA95343 United States

ISBN: (纸本)9780738131153

Unmanned aerial vehicles (UAVs) can provide vision at high altitude. In this paper, multi-UAVs and ground vehicle are utilized to explore a complex environment with obstacles. The desired UAV formation is proposed around ground vehicle to provide wider vision. The Interfered Fluid Dynamical System (IFDS) method is utilized to guide UAVs avoid obstacles, while the desired formation need be maintained. Then formation control scheme of multi-UAVs is updated to combine with IFDS method according to original formation and obstacles avoidance. Simulation results shows that multi-UAVs can avoid obstacles and maintain the desired formation around ground vehicle during exploration. © 2021 IEEE.

关键词： Ground vehicles

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VDBblox: Accurate and Efficient Distance Fields for Path Planning and Mesh Reconstruction

VDBblox: Accurate and Efficient Distance Fields for Path Pla...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Yinlong Bai Zhiqiang Miao Xiangke Wang Yong Liu Hesheng Wang Yaonan Wang Department of Electrical and Information Engineering Hunan University Changsha China College of Intelligence Science and Technology National University of Defense Technology Changsha China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Automation Shanghai Jiao Tong University Shanghai China

Highly accurate and efficient map in unknown and complex environments is essential for robotics navigation. Traditionally, mobile robot platforms are often computationally constrained when using multiple sensors to process large amounts of input data. In previous works, some of them have been deployed to embedded platforms in real-time. However, how to balance accuracy and efficiency while reducing the computational resources and the memory footprint is still the bottleneck. Motivated by these challenges, we proposed a mapping framework called VDBblox to incrementally build Euclidean Signed Distance Fields (ESDFs) map from Truncated Signed Distance Fields (TSDFs) mapping. We use a novel weight function to update the non-projective TSDFs, thus improving the quality of the mesh reconstruction with higher accuracy than up-to-date methods. Meanwhile, the generated ESDFs map is maintained by the least recently used (LRU) cache to dynamically handle the obstacle changes with less runtime than state-of-the-art. We show VDBblox performance in terms of accuracy and efficiency by benchmark comparison on RGB-D and LiDAR public datasets. Moreover, we demonstrate that VDBblox can be integrated into a completed quadrotor system as a sub-module. Then we validate it through online obstacle avoidance and high-quality mesh reconstruction in real-world experiments. Finally, we release our method as open-source code to the community 1 1 Code - https://***/yinloonga/vdbblox.

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Riemannian Online Optimistic Algorithms with Dynamic Regret

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IEEE Transactions on Automatic control 2025年

作者： Wang, Xi Yuan, Deming Hong, Yiguang Hu, Zihao Wang, Lei Shi, Guodong University of New South Wales School of Electrical Engineering & Telecommunications SydneyNSW2052 Australia Nanjing University of Science and Technology School of Automation Nanjing210094 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Hong Kong University of Science and Technology Department of Mathematics Hong Kong Zhejiang University College of Control Science and Engineering Zhejiang 310058 China The University of Sydney Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering NSW2006 Australia

In this paper, we consider Riemannian online convex optimization with dynamic regret, which involves minimizing the cumulative loss difference between a learner's decisions and a sequence of adaptive decisions across dynamic environments over time on Riemannian manifolds. First, we propose Riemannian Online Optimistic Gradient Descent (R-OOGD), which extends the classical optimistic algorithms to Riemannian manifolds, requiring one gradient inquiry per round. We then propose Riemannian Adaptive Online Optimistic Gradient Descent (R-AOOGD) by incorporating the meta-expert framework into R-OOGD. We analyze the dynamic regret of R-OOGD and R-AOOGD in terms of the regularity of the sequence of cost functions and comparators. The dynamic regret bound matches the results in Euclidean space and with a scale adjustment of O(1+κ D2/√1-KD2) related to the sectional curvature lower bound κ, sectional curvature upper bound and feasible set diameter. Finally, we provide numerical experiments to illustrate the performance of the proposed algorithms. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Research on the Startup control Method of Doubly-fed Induction Generator

Research on the Startup Control Method of Doubly-fed Inducti...

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2021 Annual Meeting of CSEE Study Committee of HVDC and Power Electronics, HVDC 2021

作者： Fang, Shiwen Zhao, Xiangyang He, Guoqing Li, Zhen State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems China Electric Power Research Institute Haidian District Beijing100192 China Beijing Institute of Technology School of Automation Haidian District Beijing100081 China School of Automation Science and Electrical Engineering Beihang University Haidian District Beijing100191 China

ISBN: (纸本)9781839537035

Aiming at the startup control issue of doubly-fed induction generator (DFIG), the startup control method of DFIG is analyzed. Based on the mathematical model of DFIG, The equivalent circuit of the grid side converter (GSC) in the uncontrolled startup period is established, and the constant dc voltage control of the GSC in the controlled startup period is obtained, realizing the startup control goal of stable dc voltage in the GSC;then the startup control strategy of the rotor side converter (RSC) is put forward, and the startup control goal of the stator winding without impulses is realized. Finally, based on MATLAB/Simulink, the simulation model of DFIG is built, and the startup process of DFIG is simulated, verifying the effectiveness of the startup control method. © 2021 IET Conference Proceedings. All rights reserved.

关键词： Equivalent circuits

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Social Force Embedded Mixed Graph Convolutional Network for Multi-class Trajectory Prediction

arXiv

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arXiv 2024年

作者： Du, Quancheng Wang, Xiao Yin, Shouguo Li, Lingxi Ning, Huansheng The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence Anhui University Hefei230031 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Electrical and Computer Engineering Indiana University Purdue University IndianapolisIN46202 United States

Accurate prediction of agent motion trajectories is crucial for autonomous driving, contributing to the reduction of collision risks in human-vehicle interactions and ensuring ample response time for other traffic participants. Current research predominantly focuses on traditional deep learning methods, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). These methods leverage relative distances to forecast the motion trajectories of a single class of agents. However, in complex traffic scenarios, the motion patterns of various types of traffic participants exhibit inherent randomness and uncertainty. Relying solely on relative distances may not adequately capture the nuanced interaction patterns between different classes of road users. In this paper, we propose a novel multi-class trajectory prediction method named the social force embedded mixed graph convolutional network (SFEM-GCN). The primary goal is to extract social interactions among agents more accurately. SFEM-GCN comprises three graph topologies: the semantic graph (SG), position graph (PG), and velocity graph (VG). These graphs encode various of social force relationships among different classes of agents in complex scenes. Specifically, SG utilizes one-hot encoding of agent-class information to guide the construction of graph adjacency matrices based on semantic information. PG and VG create adjacency matrices to capture motion interaction relationships between different classes agents. These graph structures are then integrated into a mixed graph, where learning is conducted using a spatio-temporal graph convolutional neural network (ST-GCNN). To further enhance prediction performance, we adopt temporal convolutional networks (TCNs) to generate the predicted trajectory with fewer parameters. Experimental results on publicly available datasets demonstrate that SFEM-GCN surpasses state-of-the-art methods in terms of accuracy and robustness. Copyright © 2024, The Authors.

关键词： Forecasting

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Tuning the controller of a Power Supply for an Autonomous Object

Tuning the Controller of a Power Supply for an Autonomous Ob...

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2020 International Multi-Conference on Industrial engineering and Modern Technologies, FarEastCon 2020

作者： Chekh, V. Lunkin, D. Lyapunov, D. Research Institute of Automation and Electromechanics Tomsk State University of Control Systems and Radioelectronics Tomsk Russia School of Energy and Power Engineering Tomsk Polytechnic University Research Institute of Automation and Electromechanics Tomsk State University of Control Systems and Radioelectronics Division for Power and Electrical Engineering Tomsk Russia

ISBN: (纸本)9781728169514

The paper deals with a method to tuning the controller of a power supply for an autonomous object employed for underwater exploration. The method is based on the Real Interpolation Method for the object's transfer function identification. The error of identification does not exceed 3% with respect to the response data acquired from the object. The identified transfer function is implemented to tune the controller according to one of the optimal adjustment that provides the overshooting less than 15% and the response time of 19 msec. The steady-state value is within the 10% error band in all acceptable operating modes. The method developed can be used for tuning a number of power supplies both on the designing stage and during their operation. © 2020 IEEE.

关键词： controllers

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