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Data Driven control and Learning Systems (DDCLS)

作者： Hongqiang Zhang Faxiang Zhang Jing Na Guanbin Gao Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming P. R. China Yunnan Key Laboratory of Intelligent Control and Application Kunming P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper gives an event-triggered neural tracking control strategy for cable-driven lower-limb exoskeleton robots. To reduce the number of triggers and prevent the jitter of the control signal, a switching threshold is used to drive the event trigger, which is different from the traditional trigger cases of fixed and relative thresholds. Firstly, a neural network (NN) is adopted to approximate the unknown nonlinear function, with the extracted estimation error being new leakage terms developed to update the weight of NN. Then an adaptive controller is designed to achieve the uniformly ultimately bounded(UUB) performance of the closed-loop system, and at the same time both transient and steady-state performance of the tracking error is guaranteed via a predefined performance function. Finally, the effectiveness of the proposed method is verified by simulation.

关键词： Learning systems Estimation error Simulation Exoskeletons Artificial neural networks Switches Jitter

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Automation 5.0: The Key to Systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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A Smooth Trajectory Planning for High Tibial Osteotomy Surgery with Robot-assisted Based on NURBS and S-curve Method

A Smooth Trajectory Planning for High Tibial Osteotomy Surge...

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Data Driven control and Learning Systems (DDCLS)

作者： Yuan Li Guanbin Gao Yi Bao Xinkai Chen Xinyang Guo Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming China Yunnan Key Laboratory of Intelligent Control and Application Kunming China The First People's Hospital of Yunnan Province Kunming China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Compared to conventional freehand procedures, robot-assisted surgery is more efficient and minimally invasive. The planning procedures decide the quality of robot-assisted surgery. However, the traditional polynomial function method and spline method can lead the robot to oscillate when executing the trajectory for puncture or location. To generate a smooth and steady trajectory to improve the quality of robot-assisted surgery, this paper proposes a trajectory planning method for the planning of puncture points in High Tibial Osteotomy (HTO). First, the coordinates of puncture points are obtained by creating a computer-aided design (CAD) model of the leg bone with the osteotomy plate. Then, the non-uniform rational B-spine (NURBS)method is applied to generate a smooth trajectory for puncture points. The S-curve method is used to plan the velocity and acceleration. Finally, simulations are conducted to verify the correctness and effect of the proposed method, which show that the proposed method can improve the trajectory of surgery in terms of smoothness and jerk reduction.

关键词： Solid modeling Surface reconstruction Design automation Trajectory planning Robot kinematics Surgery Trajectory

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Containment control of Multiple Quadrotor Unmanned Aerial Vehicles Based on Model Transformation

Containment Control of Multiple Quadrotor Unmanned Aerial Ve...

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Data Driven control and Learning Systems (DDCLS)

作者： Pengfei Chen Chunxi Yang Faxiang Zhang Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Yunnan P. R. China Yunnan Key Laboratory of Intelligent Control and Application Kunming P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper investigates the containment control problem of a class of quadrotor unmanned aerial vehicle (QUAV) systems under directed topologies. Firstly, an integral chain model with unknown control directions is constructed by iteratively differentiating the system output. At the same time, a low-pass filter is introduced to transform the original system into a new system, avoiding the problem of unknown control direction. Then, a distributed containment control law is designed by using the dynamic surface control method, which ensures that the trajectories of the followers converge within the convex spanned by the leaders. The closed-loop system is also proved to be uniformly ultimately bounded (UUB) based on Lyapunov stability theory. Finally, simulation results show the effectiveness of the proposed control scheme.

关键词： Simulation Low-pass filters Transforms Switches Autonomous aerial vehicles Topology Trajectory

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A Novel Remaining Useful Life Prediction Model Based on Adaptive Feature Fusion and its Application to Rolling Bearings

SSRN

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SSRN 2024年

作者： Guo, Kai Ma, Jun Wu, Jiande Xiong, Xin Faculty of Information Engineering & Automation Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming650500 China

As a key component in the transmission system of high-speed trains, once a failure occurs, it will directly affect the safety of train operation. Therefore, it is of great significance to construct a degradation index that can comprehensively characterize the running state of bearings and establish a reliable remaining useful life model to ensure the safety of train operation. Aiming at the problems that the redundant features in the existing multi-feature fusion process affect the diagnosis performance and the spurious fluctuations phenomenon of the fusion features causes the inaccurate determination of the start fault time and leads to the low prediction accuracy of remaining useful life (RUL), A method based on adaptive feature fusion and autoregressive integrated moving average model is proposed for rolling bearings prediction. The research in this study demonstrates that by comparing and verifying with two sets of public data, the proposed method is effective in accurately identifying the features that are most sensitive to degradation trends, accurately determine the initial fault moment of bearings, achieve effective prediction of the RUL of bearings, and the related research results can provide reference basis for predictive maintenance of train bearings. © 2024, The Authors. All rights reserved.

关键词： Forecasting

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Haplotype-resolved Chinese male genome assembly based on high-fidelity sequencing

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Fundamental Research 2022年第6期2卷 946-953页

作者： Xiaofei Yang Xixi Zhao Shoufang Qu Peng Jia Bo Wang Shenghan Gao Tun Xu Wenxin Zhang Jie Huang Kai Ye Genome Institute the First Affiliated Hospital of Xi'an Jiaotong UniversityXi'an 710061ShaanxiChina School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina National Institutes for food and drug Control(NIFDC) No.2Tiantan XiliDongcheng DistrictBeijing 102629China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina School of Life Science and Technology Xi'an Jiaotong UniversityXi'an 710049ShaanxiChina Faculty of Science Leiden UniversityLeidenThe Netherlands

The advantages of both the length and accuracy of high-fidelity(HiFi)reads enable chromosome-scale haplotype-resolved genome *** this study,we sequenced a cell line named HJ,established from a Chinese Han male individual by using HiFi and *** assembled two high-quality haplotypes of the HJ genome(haplotype 1(H1):3.1 Gb,haplotype 2(H2):2.9 Gb).The continuity(H1:contig N50=28.2 Mb,H2:contig N50=25.9 Mb)and completeness(BUSCO:H1=94.9%,H2=93.5%)are substantially better than those of other Chinese genomes,for example,HX1,NH1.0,and *** comparing HJ genome with GRCh38,we reported the mutation landscape of HJ and found that 176 and 213 N-gaps were filled in H1 and H2,*** addition,we detected 12.9 Mb and 13.4 Mb novel sequences containing 246 and 135 protein-coding genes in H1 and H2,*** results demonstrate the advantages of HiFi reads in haplotype-resolved genome assembly and provide two high-quality haplotypes of a potential Chinese genome as a reference for the Chinese Han population.

关键词： Genome assembly HiFi reads Human genome Haplotype-resolved Chinese Han Mutation landscape

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Perceptual Quality Evaluation of Corrupted Industrial Images 18th

Perceptual Quality Evaluation of Corrupted Industrial Images

引用

18th International Forum of Digital Multimedia Communication, IFTC 2021

作者： Gong, Yafei Peng, Chenchen Liu, Jing Zhou, Chengxu Liu, Hongyan Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China Faculty of Science Beijing University of Technology Beijing China

ISBN: (纸本)9789811922657

In recent years, computer vision applied in industrial application scenarios has been attracting attention. A lot of work has been made to present approaches based on visual perception, ensuring the safety during the processes of industrial production. However, much less effort has been done to assess the perceptual quality of corrupted industrial images. In this paper, we construct an Industrial Scene Image Database (ISID), which contains 3000 distorted images generated through applying different levels of distortion types to each of the 50 source images. Then, the subjective experiment is carried out to gather the subjective scores in a well-controlled laboratory environment. Finally, we perform comparison experiments on ISID database to investigate the performance of some objective image quality assessment algorithms. The experimental results show that the state-of-the-art image quality assessment methods have difficulty in predicting the quality of images that contain multiple distortion types. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Database systems

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Autonomous Vehicle Drift With a Soft Actor-critic Reinforcement Learning Agent 20

Autonomous Vehicle Drift With a Soft Actor-critic Reinforcem...

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20th IEEE Jubilee World Symposium on Applied Machine Intelligence and Informatics, SAMI 2022

作者： Hunor Toth, Szilard Janos Viharos, Zsolt Bardos, Adam Institute of Computer Science and Control Research Laboratory on Engineering Management Intelligence Intelligent Processes Research Group Budapest Hungary John von Neumann University Faculty of Economics Kecskemét Hungary Budapest University of Technology and Economics Department of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665497046

Self-driving vehicles have become a more and more important field in recent years. Supported by the techniques of Artificial Intelligence (AI), the current tendency of positive results in applications is making it a promising area to focus further research. Additionally, Reinforcement Learning (RL) is already proved to be an efficient approach for complex problems, e.g. robots, industrial systems and also games (like chess, Go), *** is a driving technique at handling limits where the driver intentionally oversteers, with loss of traction, while driving the vehicle through the entirety of a corner. It is a very challenging control task and often results in an accident when it occurs on public roads, consequently, the efficient control of this motion is especially important in the safety of autonomous *** paper reports novel research results whose main goal is to develop a self-driving agent for drift motion control based on vehicle simulation by Matlab/Simulink. Longitudinal and lateral velocity together with the yaw rate formed the state representation of the vehicle. The agent action space consists of two continuous actuator values: pedal ratio and roadwheel angle. The goal of the agent is twofold: first, it has to jump into a drifting state, second, it has to keep the vehicle in *** simulation results show that the proposed Soft Actor-Critic (SAC) RL agent is capable of learning to approach a pre-determined drift equilibrium from cornering and staying in this drift situation as well. For the training, the solution excluded using any kind of prior data, it only works with information gained from the simulation model, which is a remarkable difference from the actual state-of-the-art RL-based solutions. © 2022 IEEE.

关键词： Training Roads Simulation Reinforcement learning Mathematical models Data models Artificial intelligence

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Infrared Video Data Cleaning Based on LightWeight CNN-LSTM

Infrared Video Data Cleaning Based on LightWeight CNN-LSTM

引用

2023 China Automation Congress, CAC 2023

作者： Liu, Fang Li, Shiwei Chen, Congang Hu, Yutong Gong, Hua College of Science Shengyang Ligong University Liaoning Key Laboratory of Intelligent Optimization and Control for Ordnance Industry Shenyang110159 China School of Automation and Electrical Engineering Shengyang Ligong University Shenyang110159 China Beijing Normal University - Hong Kong Baptist University United International College Faculty of Science and Technology Zhuhai519087 China National Key Laboratory of Electromagnetic Space Security Tianjing300308 China

ISBN: (纸本)9798350303759

Video cleaning is a pivotal technology for enhancing the quality of infrared video data. In order to achieve high-quality cleaning of infrared video data, the temporal correlation features in the video data are thoroughly taken into account. A feature extraction model is designed. This model integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory Networks (LSTM). It can extract infrared video features in both spatial dimension and temporal dimension. Considering the characteristics of low resolution and weak feature information in infrared video images, a lightweight strategy is adopted to achieve high-quality extraction of weak information in infrared images. In this paper, an infrared video data cleaning model lightweight CNN-LSTM is developed by incorporating a lightweight strategy and video spatiotemporal features. Through seven experimental comparisons, the model utilized in this study achieved improvement ranges of 0.6% to 43.8% in accuracy and 0.7% to 65.7% in recall. © 2023 IEEE.

关键词： Long short-term memory

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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

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IEEE Transactions on control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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