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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shanghai Friendess Electronic Technology Shanghai201100 China

In this article, the complicated task assignment, scheduling and planning of heterogeneous multi-robot welding process are studied. Firstly, for large-scaled tasks that involve heterogeneous multi-robot task allocation under different internal and external constraints, the traditional multi-robot task allocation (MRTA) framework is extended to a novel and unified heterogeneous multi-robot task allocation (H MRTA)***,robotsofdifferentconfigurations (including manipulators, positioners, gantries) are treated as unified robots. Secondly, taking into account constraints such as reachability, collision avoidance, kinematic and dynamic process constraints, the optimization model based on H-MRTA framework is established. The optimization objectives are formulated by combining the total execution time and load balance between robots. Then, a hierarchical optimization algorithm(TCO-HMRTA) is proposed to solve the H-MRTA problem with decoupled two-layer optimization sub-problems : task space segmentation subproblem and multi-robot path planning subproblem. For the task space segmentation subproblem, a task-centered optimization model is established, which aims to balance the workload among robots, considering the competition and cooperation between robots. For the multi-robot path planning problem, multiple process constraints are considered and the total working time is minimized as the objective function. Finally, The effectiveness of the optimization algorithm is verified by a case study on the welding task of a large plate element in a ship hull. Compared to two other state-of-the-art algorithms, TCO-HMRTA can save more than 50% of the waiting time and 10%-20% of the execution time, which demonstrates the effectiveness and feasibility of the hierarchical optimization-based task allocation algorithm for complicated heterogeneous multi-robots. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Anomaly detection in digital twin model 1

Anomaly detection in digital twin model

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Wang, Yutong Cao, Yansong Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665433372

As the simulation model of a physical system, digital twin has been widely used in many complicated control systems. Providing an effective way to perform simulation, digital twin makes the evaluation, prediction and optimization process cheaper and easier than on physical systems. For smart manufacturing, digital twin achieves high productivity with less operation and maintenance cost. However, the advantages of digital twin in anomaly detection during manufacturing are always neglected. Taking a two-speed transmission system as an example, we generate three kinds of faults on this digital twin model. After extracting features from the system output, we train an anomaly detection model on these features to classify each type of fault. By this digital twin model, we can find the fault in the whole system at the very beginning, and reduce the time and cost of debugging and diagnosing. © 2021 IEEE.

关键词： Anomaly detection

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An Error Correcting Output Code Algorithm Based on Hierarchical Clustering for Lithology Identification

An Error Correcting Output Code Algorithm Based on Hierarchi...

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Chinese control Conference (CCC)

作者： Ao Li Xi Chen School of Rail Transit Hunan University of Technology Zhuzhou China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm, the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.

关键词： Codes Accuracy Geology Clustering algorithms Binary trees Encoding Classification algorithms

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Double wavelet threshold filter design for real-time adaptive denoising in OA-ICOS

Double wavelet threshold filter design for real-time adaptiv...

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Jiangsu Annual Conference on Automation (JACA 2024)

作者： Yixin Deng Zairan Wang Yang-Yang Chen Qin Liu Xiangyu Wang School of Automation and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing People's Republic of China School of Cyber Science and Engineering Southeast University Nanjing People's Republic of China

ISBN: (数字)9781837242719

In the Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) technique, single-stage filters are commonly used to reduce noise and improve the signal-to-noise ratio, enabling more precise CO2 concentration detection. However, these filters often underperform under real-time conditions. To enhance real-time performance, this paper proposes a novel framework based on Double Wavelet Threshold Filter (DWTF) that adaptively suppresses noise while preserving key features of CO2 concentration signal. Firstly, one wavelet threshold filter (WT) is introduced to calculate the mean of the current sequence, providing an initial denoising step. Secondly, another WT is employed to extract features from a longer sequence for adaptive computation of the discount factor. Finally, an exponential moving average filter (EMA) is applied to combine both current and historical data to produce a smoother aggregated output. To validate the effectiveness, DWTF was compared with other conventional algorithms for a CO2 dataset with three distinct states: smooth, ship and mutant, obtained by OA-ICOS. The experimental results demonstrate that DWTF performs effectively in all three states.

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Differential Steering control for 6 × 6 Wheel-drive Mobile Robot 26

Differential Steering Control for 6 × 6 Wheel-drive Mobile ...

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26th International Conference on Automation and Computing, ICAC 2021

作者： Zhao, Hongqiang Luo, Chao Xu, Yongkang Li, Jiehao Central South University State Key Laboratory of High Performance Complex Manufacturing School of Mechanical and Electrical Engineering ChangSha China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing China

ISBN: (纸本)9781860435577

The 6 × 6 Wheel-drive mobile robot is widely used in the field of special operations, and there is the phenomenon of slipping in the process of steering. To study the steering accuracy and stability of mobile robot, the dynamic model of 6 × 6 Wheel-drive Mobile Robot is established, and the sliding mode control strategy of differential steering based on mobile robot is proposed. Firstly, taking the torque of six wheels and the operator's direction control as input, the three-dimensional attitude and the relative position of the steering center of the mobile robot are obtained by using the position and attitude sensor, to determine the reference steering angle of the mobile robot. Secondly, considering the relationship between the position error and the velocity error, a recursive sliding surface is designed, and a neural network is introduced to approach the uncertain part of the mobile robot model. Then, a nonlinear gain function is applied to construct a dynamic surface control law. Finally, through the Trucksim/Simulink co-simulation model, the nonlinear gain recursive sliding mode dynamic surface adaptive control method for mobile robot trajectory tracking can improve the tracking speed and control precision, and the control force and torque are smooth and reasonable. The results show that the method is effective in improving the steering accuracy and stability of mobile robot. © 2021 Chinese Automation and Computing Society in the UK-CACSUK.

关键词： Mobile robots

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A KDC-enhanced closest point method for thermal analysis on curved geometries using LS-GFDM

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Applied Mathematics Letters 2025年 171卷

作者： Tang, Zhuochao Gu, Jiming Chen, Bin Fu, Zhuojia School of Management Science and Engineering Anhui University of Technology Maanshan243002 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Maanshan243002 China Center for Numerical Simulation Software in Engineering and Sciences College of Mechanics and Engineering Science Hohai University Nanjing211100 China

This paper presents a Krylov-deferred correction (KDC)-enhanced closest point method (CPM) integrated with the least-squares generalized finite difference method (LS-GFDM) for thermal analysis on curved geometries. To overcome the inherent limitations of conventional single-step/multi-step temporal schemes in long-time simulations, we systematically unify three advanced components: (i) CPM's embedding strategy that transforms surface PDEs into extended problems over Cartesian grids, (ii) LS-GFDM's spatial discretization employing dual point sets to enhance applicability beyond conventional GFDM, and (iii) KDC's predictor–corrector framework that iteratively refines temporal solutions to achieve high-order accuracy. Building upon our previous work (Tang et al. 2025) where LS-GFDM was integrated with CPM using explicit Euler temporal schemes, this study constitutes a critical advancement by replacing low-order temporal discretization with the KDC methodology. Numerical experiments demonstrate that our KDC-CPM-LSGFDM framework achieves superior numerical performance. © 2025 Elsevier Ltd

关键词： Least squares approximations

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Tunable and Functional Ionic Liquids Embedded Hyper-Crosslinked Polymers as H2o-Tolerant Adsorbents for Highly Efficient Gaseous Toluene Capture

SSRN

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SSRN 2024年

作者： Nie, Xiongfei Qiu, Xinjie Zhang, Ruina Ke, Quanli Liu, Huayan Zhang, Xiangping Lu, Hanfeng Cui, Guokai Zhang, Suojiang Innovation Team of Air Pollution Control Institute of Catalytic Reaction Engineering State Key Laboratory Breeding Base of Green Chemistry Synthesis Technology College of Chemical Engineering Zhejiang University of Technology Hangzhou310014 China Beijing Key Laboratory of Ionic Liquids Clean Process CAS Key Laboratory of Green Process and Engineering State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

Developing advanced sorbents for efficient aromatic VOCs sorption from humid conditions are highly desired. In this work, a series of tunable and functional ionic liquids embedded hyper-crosslinked polymers (ILHCPs) containing different structures of anion-functional ionic liquids (ILs) with 1,4-dichloroxylene (DCX) as the crosslinker were designed and prepared for highly efficient gaseous toluene adsorption under humidity. These ILHCPs could achieve high surface area (600~900 m2 g−1), high micropore volume (0.1~0.3 cm3 g−1), small average pore size (4~5 nm), and large water contact angle (up to 110°) through tuning the anion structures and the initial IL:DCX molar ratio. Gaseous toluene adsorption isotherms on typical ILHCPs were tested under 298, 308, and 318 K, and a dual-site Langmuir-Freundlich (DSLF) model was used for well describing adsorption isotherms, which can be divided into two contributions for site I and site II. The isosteric heats of gaseous toluene adsorption were calculated. Furthermore, toluene adsorption under different humidity conditions were also tested. Compared with DCX-based self-condensed HCP, toluene adsorption capacity of ILHCPs remained steadily (270 mg g−1) even under 80% humidity. To our best knowledge, this is the first example of tuning functional ILHCPs for efficient H2O-tolerant gaseous toluene adsorption. The method may also open a door to achieving high adsorption efficiency of other volatile organic compounds by functional IL-based porous materials. © 2024, The Authors. All rights reserved.

关键词： Gas adsorption

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Challenges of simulating fluid flows on near-term quantum computer

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SCIENCE CHINA Physics, Mechanics & Astronomy 2025年第10期68卷 1-2页

作者： Zhaoyuan Meng Chao Song Yue Yang State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing 100871 China School of Physics ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang Key Laboratory of Micro-nano Quantum Chips and Quantum Control Zhejiang University Hangzhou 310027 China HEDPS-CAPT Peking University Beijing 100871 China

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Adapting Human Mesh Recovery with Vision-Language Feedback

arXiv

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arXiv 2025年

作者： Xu, Chongyang Huang, Buzhen Zhang, Chengfang Feng, Ziliang Wang, Yangang College of Computer Science Sichuan University Chengdu610065 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The School of Automation Southeast University Nanjing210096 China Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Luzhou646000 China

Human mesh recovery can be approached using either regression-based or optimization-based methods. Regression models achieve high pose accuracy but struggle with model-to-image alignment due to the lack of explicit 2D-3D correspondences. In contrast, optimization-based methods align 3D models to 2D observations but are prone to local minima and depth ambiguity. In this work, we leverage large vision-language models (VLMs) to generate interactive body part descriptions, which serve as implicit constraints to enhance 3D perception and limit the optimization space. Specifically, we formulate monocular human mesh recovery as a distribution adaptation task by integrating both 2D observations and language descriptions. To bridge the gap between text and 3D pose signals, we first train a text encoder and a pose VQ-VAE, aligning texts to body poses in a shared latent space using contrastive learning. Subsequently, we employ a diffusion-based framework to refine the initial parameters guided by gradients derived from both 2D observations and text descriptions. Finally, the model can produce poses with accurate 3D perception and image consistency. Experimental results on multiple benchmarks validate its effectiveness. The code will be made publicly available. © 2025, CC BY.

关键词： Mesh generation

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An Efficient Learning control Framework with Sim-to-Real for String-Type Artificial Muscle-Driven Robotic systems

arXiv

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arXiv 2024年

作者： Tao, Jiyue Zhang, Yunsong Rajendran, Sunil Kumar Zhang, Feitian The Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering the State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China The BSS Technologies Inc. Takoma ParkMD20912 United States

Robotic systems driven by artificial muscles present unique challenges due to the nonlinear dynamics of actuators and the complex designs of mechanical structures. Traditional model-based controllers often struggle to achieve desired control performance in such systems. Deep reinforcement learning (DRL), a trending machine learning technique widely adopted in robot control, offers a promising alternative. However, integrating DRL into these robotic systems faces significant challenges, including the requirement for large amounts of training data and the inevitable sim-to-real gap when deployed to real-world robots. This paper proposes an efficient reinforcement learning control framework with sim-to-real transfer to address these challenges. Bootstrap and augmentation enhancements are designed to improve the data efficiency of baseline DRL algorithms, while a sim-to-real transfer technique, namely randomization of muscle dynamics, is adopted to bridge the gap between simulation and real-world deployment. Extensive experiments and ablation studies are conducted utilizing two string-type artificial muscle-driven robotic systems including a two degree-of-freedom robotic eye and a parallel robotic wrist, the results of which demonstrate the effectiveness of the proposed learning control strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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