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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Hou, Jake Jie Wu, Xinrui Shan, Jiwei Li, Dun Wang, Hesheng Shanghai Jiao Tong University Department of Automation China Shanghai Karlang Industrial Nantong Intelligent Technology Co. Ltd China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

SLAM is significant to autonomous mobile robots. In order to realize drift-free state estimation and provide accurate localization results for the subsequent navigation, we develop an optimization-based framework consisting of a high-frequency Inertial-Wheel Odometry(IWO), Visual-Inertial-Wheel Odometry(VIWO) and a global fusion module. To fuse the local state with the position provided by GNSS, we perform ternary edge in factor graph optimization to estimate the transformation between the local frame and ENU coordinate. Thanks to the tightly-coupled VIWO, the localization property of the odometry presents more robustness, and improve the accuracy of global fusion. A noise repropagation strategy is introduced to ensure the consistency of the IMU and wheel odometer. We evaluate the proposed system on public datasets and test it in real-world scenario. The experimental results show that our system achieves accurate pose estimation in outdoor environments. © 2022 IEEE.

关键词： Frequency estimation

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Multi-objective Group Decision and Cooperative Planning Based on Preference and Fuzzy Measure 1

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

作者： Ma, Xiwen Xie, Wei Yang, Jingsong Zhang, Weidong Lu, Jinhui School of Oceanography Shanghai Jiao Tong University Shanghai China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou China Department of Automation Shanghai Jiao Tong University Shanghai China Zhuhai China School of Information and Communication Engineering Hainan University Hainan Haikou China National Engineering Research Center of Ship and Shipping Control System Shanghai China Crossocean of Suzhou technology No. 218 East Oingdao Road Suzhou China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

To pursue interest balance and improve collaboration efficiency, this paper proposes a multi-agent cooperation method integrating decision-making and planning. Based on preference and fuzzy measures, this method can balance individual and group benefits under fuzzy uncertain environment. The equilibrium solution of a multi-agent multi-objective game, namely group decision-making (GDM) solution, can be obtained by the Gaussian oscillation particle swarm optimization (GOPSO) algorithm, which overcomes the dilemma of a multi-objective group game and improves the computational efficiency. Considering the smoothness and continuity of the trajectory, a heuristic motion planning (MP) generation model that satisfies the kinematic constraints and minimizes differential thrust is proposed, which improves the cooperation efficiency. To verify the performance of this proposed method, simulation results are presented and some comparative statements are given. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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Input and state constrained inverse optimal control with application to power networks

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IFAC-PapersOnLine 2023年第2期56卷 5451-5456页

作者： Taouba Kaouther Jouini Zhiyong Sun Venkatraman Renganathan Veit Hagenmeyer Institute of Automation and Applied Informatics (IAI) at Karlsruhe Institute of Technology Germany Department of Electrical Engineering Eindhoven University of Technology Netherlands Department of Automatic Control LTH Lund University Sweden

We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set and the initial input lies on an ellipsoid inside the input constraint set, we show that the stabilizing controller solves the constrained optimal control problem. Compared to the state-of-the-art, we avoid solving nonlinear optimization problems evaluated pointwise, i.e., for every state, or in a repetitive fashion, i.e., at each time step. We apply our theoretical results to study the angular droop control studied in (Jouini et al., 2022) of an inverter-based power network. For this, we accommodate the constraints on the angle and power generation and exemplify our approach through a two-inverter case study.

关键词： Optimal control Non-Linear control systems Networked systems Power and Energy systems

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An event-triggered tracking control scheme based on predictive control method and its application

An event-triggered tracking control scheme based on predicti...

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第42届中国控制会议

作者： Lei Cao Erhan Yumuk Clara-Mihaela Ionescu Guo-Ping Liu Department of Control Science and Engineering Harbin Institute of Technology Dynamical Systems and Control Research Group Department of Electromechanical Systems and Metal Engineering Ghent University Department of Control and Automation Engineering Istanbul Technical University Center for Control Science and Technology Southern University of Science and Technology

In this paper, the tracking control problem for networked control system(NCS) under communication delays is investigated. In order to realize the tracking of the NCS, an event-triggered predictive control strategy is provided to compensate for the delays and achieve stability. Both tracking performance and input increments are considered in the proposed cost *** on the incremental inputs, an event-triggered mechanism is established to reduce the communication costs. The efforts of different parameters are illustrated through the results of the simulation, and the effectiveness of the proposed control scheme is also validated from the application of the networked lighting setup.

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A Real-Time FPGA-Based Edge Computing Approach for Pedestrian Trajectory Prediction

A Real-Time FPGA-Based Edge Computing Approach for Pedestria...

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IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Wen-Hui Chen Zong-Hua Ho Yu-Chen Lin Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (数字)9798331535537

ISBN: (纸本)9798331535544

This study presents an FPGA-based edge computing solution for real-time pedestrian trajectory prediction in autonomous driving applications. The system integrates three key components: pedestrian detection using the YOLOv5m model, multi-object tracking with ByteTrack, and trajectory prediction. To address the computational constraints of edge devices, we employ model compression techniques including channel pruning and quantization. Our implementation on the Xilinx ZCU104 platform demonstrates significant improvements in computational efficiency: the detection model achieves an 85% reduction in parameters while maintaining robust performance with only a 0.5% decrease in mAP, and increases inference speed from 19.03 FPS to 32.18 FPS. The complete system achieves real-time trajectory prediction performance suitable for autonomous driving applications. This work advances the field of sustainable edge computing by effectively balancing computational efficiency, prediction accuracy, and real-time performance requirements for safety-critical autonomous driving systems.

关键词： Pedestrians Quantization (signal) Conferences Computational modeling Real-time systems Trajectory Computational efficiency Autonomous vehicles Field programmable gate arrays Edge computing

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Optimal Strategies Trajectory with Multi-Local-Worlds Graph

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Computers, Materials & Continua 2023年第4期75卷 2079-2099页

作者： Xiang Yu Chonghua Wang Xiaojing Zheng Chaoyu Zeng Brij BGupta School of Electronics and Information Engineering Taizhou UniversityTaizhouZhejiang318000China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China School of Economics and Management Weifang University of Science and TechnologyShouguangShandong262700China National Computer System Engineering Research Institute of China Beijing102699China Department of Computer Science and Information Engineering Asia UniversityTaiwanTaichung413China Research and Innovation Department Skyline University CollegeSharjahP.O.Box 1797United Arab Emirates Staffordshire University Stoke-on-TrentST42DEUK

This paper constructs a non-cooperative/cooperative stochasticdifferential game model to prove that the optimal strategies trajectory ofagents in a system with a topological configuration of a Multi-Local-Worldgraph would converge into a certain attractor if the system’s configuration isfixed. Due to the economics and management property, almost all systems aredivided into several independent Local-Worlds, and the interaction betweenagents in the system is more complex. The interaction between agents inthe same Local-World is defined as a stochastic differential cooperativegame;conversely, the interaction between agents in different Local-Worldsis defined as a stochastic differential non-cooperative game. We construct anon-cooperative/cooperative stochastic differential game model to describethe interaction between agents. The solutions of the cooperative and noncooperativegames are obtained by invoking corresponding theories, and thena nonlinear operator is constructed to couple these two solutions *** last, the optimal strategies trajectory of agents in the system is proven toconverge into a certain attractor, which means that strategies trajectory arecertainty as time tends to infinity or a large positive integer. It is concluded thatthe optimal strategy trajectory with a nonlinear operator of cooperative/noncooperativestochastic differential game between agents can make agentsin a certain Local-World coordinate and make the Local-World paymentmaximize, and can make the all Local-Worlds equilibrated;furthermore, theoptimal strategy of the coupled game can converge into a particular attractorthat decides the optimal property.

关键词： Multi-Local-world graph stochastic differential game optimal strategy attractor

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Asynchronous distributed charging protocol for plug-in electric vehicles

Journal of Economy and Technology

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Journal of Economy and Technology 2023年 1卷 29-47页

作者： Yunfan Zhang Yifan Su Yue Chen Feng Liu State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing China China Electric Power Planning & Engineering Institue Beijing China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Special Administrative Region China

The proliferation of plug-in electric vehicles (PEVs) advocates a distributed paradigm for coordinating PEV charging. Unlike existing primal-dual decomposition or consensus methods, this paper proposes a cutting-plane-based distributed algorithm considering a peer-to-peer (P2P) communication network, which enables asynchronous coordination among PEVs. First, an equivalent surrogate model is established by exploiting the duality of the original optimization problem, which masks the private information of individual users by equivalent transformation. Then, a cutting-plane based algorithm is derived to solve the surrogate problem in a distributed manner with intrinsic superiority to cope with various asynchrony. Critical implementation issues, including distributed initialization, distributed cutting-plane generation, and localized stopping criteria, are discussed in detail. Numerical tests on IEEE 37- and 123-node feeders with actual data illustrate that the proposed method is resilient to several asynchronies and admits the plug-and-play operation mode. The proposed methodology is expected to provide an alternative path toward the robust protocol for PEV charging.

关键词： Asynchronous algorithm Charging protocol Distributed optimization Plug-in electrical vehicles

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Prediction of second-order rate constants between carbonate radical and organics by deep neural network combined with molecular fingerprints

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Chinese Chemical Letters 2022年第1期33卷 438-441页

作者： Peizhe Sun Huixin Ma Shangyu Li Hong Yao Ruochun Zhang School of Environmental Science and Engineering Tianjin UniversityTianjin 300072China School of Civil Engineering Tianjin UniversityTianjin 300072China Beijing Key Laboratory of Aqueous Typical Pollutants Control and Water Quality Safeguard Department of Municipal and Environmental EngineeringSchool of Civil EngineeringBeijing Jiaotong UniversityBeijing 100044China Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China Tianjin Key Laboratory of Earth Critical Zone Science and Sustainable Development in Bohai Rim Tianjin UniversityTianjin 300072China

Carbonate radical is among the most important environmental relevant reactive species which govern the transformation and fate of pharmaceutical contaminants(PCs).However,reaction rate constants between carbonate radical and most of the PCs have not been experimentally determined,and quantitative structural-activity relationships(QSARs)have not been established for rate *** study applied Max Min data processing method and used molecular fingerprints(MF)as the input of a deep neural network(DNN)to predict the rate constants between carbonate radical and organic *** parameters and the hyper-structure of the DNN were adjusted to yield satisfactory accuracy of rate *** vector length of 512 bits with radius of 1 for MF and 5 hidden layers gave the best *** optimized MaxMin-MF-DNN model was compared with some of the most commonly used QSARs and machine learning methods,including random data splitting,molecular descriptors,supporting vector machine,decision tree,*** showed that the MF-DNN model out-performed the other methods by more than 10%increase in prediction *** this MF-DNN model,we estimated reaction rates between carbonate radical and pharmaceuticals used in human medicine(1576)and veterinary practice(390).Among them,46 drugs were identified as fast-reacting compounds,suggesting the important relations of their environmental fate with carbonate radical.

关键词： Deep neural network Carbonate radical Molecular fingerprints QSAR Pharmaceuticals

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Investigation of a Simulated Robot Model when it is Trained to Set Trajectories in the Task of controlling Assembly Parameters at Remote Visualization

Investigation of a Simulated Robot Model when it is Trained ...

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2022 International Russian automation Conference, RusAutoCon 2022

作者： Malkarov, A.Yu. Arkhipov, M.V. Kocherevskaya, L.B. Moscow Polytechnic University Faculty of Mechanical Engineering Department of Automation and Control Moscow Russia Moscow Aviation Institute National Research University Foreign Language Department for Aerospase Specialities Moscow Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

The science of robotics is becoming more and more relevant for industrial production. Visualization of the production system involves the exact modeling of its components as accurately as possible. For a robotic technological complex, such a main component is an industrial robot. The robot model should most accurately reflect what is happening in real production, since the robot is the basis of robotic production. Modeling allows you to perform a comprehensive analysis of the production system without direct design and start-up and, if possible, easily redesign it. An application was developed for building a virtual model of the robot and the workspace. An analysis of the behavior of the manipulator makes it possible to consistently improve the accuracy of modeling and the efficiency of designing a robotic technological complex. © 2022 IEEE.

关键词： Visualization

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Evaluating the Influence of Object Detection Models and Dataset Selection on Traffic Accident Prediction Performance

Evaluating the Influence of Object Detection Models and Data...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Chen, Wen-Hui Huang, Yu-Hung Lin, Yu-Chen Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9798331521165

Traffic accidents pose significant social and economic challenges, making effective accident prediction systems essential. Traditional machine learning methods often struggle to capture the complex, nonlinear patterns in visual accident data. Recent advancements suggest that deep learning offers a promising solution to this challenge. These vision-based systems rely on object detection as a foundational step, identifying key entities in traffic scenes captured by cameras to improve prediction accuracy. Despite its importance, the impact of object detection accuracy on overall accident prediction effectiveness remains underexamined. This study investigates this relationship through cross-dataset analysis. Experimental results show that object detection accuracy directly impacts accident prediction performance, with training dataset choice playing a critical role. Enhancing model generalization is essential to stabilizing accident prediction systems. © 2025 IEEE.

关键词： Highway accidents

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