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IEEE International Conference on systems, Man and Cybernetics

作者： Hongyu Zhao Zhelong Wang Sen Qiu Xin Shi Ruichen Liu Jianjun Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and with the School of Control Science and Engineering Dalian University of Technology Dalian China Beijing Institute of Spacecraft System Engineering Beijing China

Gait analysis based on wearable inertial sensors is conceptually well known, which has potential use in various applications related to gait patterns. However, as such systems are inherently nonlinear, their performance characteristics with respective to system settings are loosely researched and poorly documented. Literature in this area mainly focuses on improving system accuracy by fusing complex algorithms and additional sensors, against their gold standard counterparts, such as optical motion capture systems and force plates. This paper addresses the issue of how the system accuracy changes as the parameter settings change, and what system accuracy can be obtained by parameter tuning. A conventional feedforward neural network (FNN) is adopted to detect the temporal gait features that are prerequisite for gait analysis, and a six-phase gait model is adopted to give a close examination of human gait. In general, three main parameters are related to the FNN-based detection algorithm, i.e., the number of network layers, the number of neurons in each hidden layer, and the size of sliding window. The roles of these parameters are analyzed, and their effects on system accuracy is evaluated with multi-subject data, to offer some suggestions for parameter tuning and facilitate the system implementation.

关键词： Hidden Markov models Optical sensors Feature extraction Training Data acquisition Foot

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Design and Fabrication of Silo Cleaning Robot Using Vacuum Principle

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Journal of Physics: Conference Series 2021年第1期1922卷

作者： Chi-Cong Nguyen Van-Tinh Nguyen Ngoc-Linh Tao Thanh-Trung Nguyen Ngoc-Kien Nguyen Ngoc-Tam Bui Department of Mechanical Engineering Viettel High Technology Industries Corporation Vietnam. School of Mechanical Engineering Hanoi University of Science and Technology Vietnam. Department of Machinery and Control System Shibaura Institute of Technology Japan.

This paper presents a mechanical design and motion-control system of a Wall-Climbing Robot (WCR) which can move on the silo's surface for cleaning purposes. One of the most challenges with this type of robot that the researchers confront is how to keep the robot moving steadily on the wall with the most optimal approach. In this study, a new mechanical design of the Wall-Climbing robot using the Vacuum principle and wireless control technology were proposed. This version of the robot enhances the ability of its movement on the silo's wall and optimizes control system. In detail, the Minimum Required Adhesion Force (FMRA) is calculated to be balanced with gravity and its torque. Moreover, a Wireless control system (WCS) is designed to drive the Robot remotely. The optimal control trajectory and velocities are given based on theory calculations and comparisons.

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Improved K-medoids clustering based on gray association rule

Improved K-medoids clustering based on gray association rule

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International Conference on Intelligent Computing, Communication and Devices, ICCD 2017

作者： Gao, Shiying Zhou, Xiaofeng Li, Shuai Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang110016 China School of Computer Science and Engineering Northeastern University Shenyang110000 China

ISBN: (纸本)9789811089435

This paper presents a new K-Medoids clustering algorithm based on gray relational degree. Analyze the gray incidence of each attribute and convert them into the weights of the attributes, and then apply these weights to the distance measure of the cluster;based on this measure, this paper proposed an improved clustering algorithm: Gray-K-Medoids clustering algorithm and applied it to the analysis of the aluminum electrolysis data. The paper introduces the gray relational degree and the basic principle based on the gray relational degree clustering and introduced the improved algorithm in detail. In order to test the effect of improving the algorithm, it was used to the production data of an aluminum plant, and the results show the effectiveness of the algorithm, has a certain promotional value. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Clustering algorithms

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Superplastic behavior of Al-Mg-Mn alloy: An experimental & numerical investigation 15th

Superplastic behavior of Al-Mg-Mn alloy: An experimental & n...

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15th International Symposium on Advanced Materials, ISAM 2017

作者： Tayyaba, Zaman Rehan, Qayyume Amjad, Ali Shaheed, Khan Chaoli, Maa Institute of Industrial Control System Rawalpindi Pakistan School of Material Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9783035711974

Deformation response of Al-4.46Mg-0.48Mn alloy under uniaxial tensile loading was investigated at temperatures ranging from 400-525°C and at strain rates of 3 × 10-3s-1, 10-3s-1 and 10-4s-1. The alloy exhibited a maximum elongation >480% at a strain rate of 10-3s-1 and 525°C. At all conditions, the dominant deformation mechanism governing the superplastic deformation was investigated as a function of strain rate and temperature. The contributions of strain-rate sensitivity and strain hardening were analyzed in relation to the observed tensile ductility. The strain rate sensitivity index (m) and average activation energy (Q) values revealed that the dominant deformation mechanism was grain boundary sliding (GBS). The GBS phenomenon was further confirmed through high magnification examination of deformed surface. Optical microscopy (OM) and Scanning Electron Microscopy (SEM) showed that dynamic re-crystallization occurs during hot deformation of the alloy which causes reasonable enhancement of plasticity. © 2018 Trans Tech Publications, Switzerland.

关键词： Ternary alloys

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Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy

Robotic Electrospinning Actuated by Non-Circular Joint Conti...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zicong Wu Chuqian Lou Zhu Jin Shaoping Huang Ning Liu Yun Zou Mirko Kovac Anzhu Gao Guang-Zhong Yang Shanghai Jiao Tong University Shanghai P. R. China Imperial College London and Empa-Swiss Federal Laboratories for Materials Science and Technology Precision Robotics (Hong Kong) Limited Hong Kong China Aerial Robotics Laboratory Imperial College London London United Kingdom Shanghai Jiao Tong University and the Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai P. R. China

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments.

关键词： Drugs Electric potential Fluids Tissue engineering Medical treatment Bending Manipulators

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NU-WAY, an Application of Numerical Methods in Campus Running Route Evaluation

NU-WAY, an Application of Numerical Methods in Campus Runnin...

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2018 Chinese Automation Congress, CAC 2018

作者： Xianghao, Zhan Xikai, Yang Jianming, Zhang College of Control Science and Engineering Zhejiang University Hangzhou China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Institute of Intelligent System and Control of Zhejiang University Hangzhou China

ISBN: (纸本)9781728113128

Over the years, campus circulatory run and campus marathons have gone viral in many Chinese universities, which calls for the accuracy of route measurement. Traditional methods of distance measurement apply GPS positioning and distance evaluation, which is more displacement-based, leading to our thinking whether it is applicable to solve distance measurement from speed with numerical methods. Meanwhile, many popular sporting applications on phones and GPS provide ways for relative accurate speed measurement. Therefore, this work integrates sporting applications with numerical fitting and integration methods to calculate the circumference of campus and used Zijingang Campus of Zhejiang University as an example. With such methods as Least Square Fitting, Compound Trapezoid Integration, Compound Simpson Integration and Romberg Integration applied, the results indicate the circumference of Zijingang Campus ranges from 3758.18m to 3767.13m, corresponding well with the results given by GPS-based sporting application, which shows the effectiveness of numerical analytical methods. © 2018 IEEE.

关键词： Numerical methods

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Time consistency technique of multi-aircrafts simulation system for cooperative mission

Time consistency technique of multi-aircrafts simulation sys...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jian Han Hang Shi JiaHui Tong Qing Zhang Jing Li Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Aiming at the problem of time inconsistency problem exposed in multi-aircrafts simulation system during executing cooperative mission, a control solution of time consistency has been proposed to realize the unity of time information. On the basis of thoroughly analyzing the components and features of system, the factors that affect time synchronization are summarized and classified. After embedding a hardware of time synchronization system, a control solution is devised to maintain time consistency. Time synchronization and delay compensation are achieved from two aspects of hardware and software, which provides technical support for the following development and verification of cooperative control technology based on multiaircrafts simulation system.

关键词： Cascading style sheets Synchronization Delays Clocks Benchmark testing Delay effects

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Finite Time Cooperative Guidance Law for Multiple UAVs with Intermittent Communication Topologies

Finite Time Cooperative Guidance Law for Multiple UAVs with ...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Teng LYU Cheng XU Hongchun LI Song HU Daochi ZHANG Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (纸本)9781728137933

To solve the problem of multiple Unmanned Aerial Vehicles (UAVs) with intermittent communication topologies simultaneously attack a stationary target, a time cooperative guidance law is studied in this paper. First, a novel time cooperative guidance model for multiple UAVs is constructed based on UAVs-target relative motion equations. Then, a cooperative guidance law is designed based on consensus theory, which can ensure multiple UAVs' impact times realize finite time consensus under intermittent topologies. After UAVs' impact times become to be the same, traditional PN guidance law is applied in all UAVs to guarantee that the UAVs can attack the target precisely without influencing the consensus of impact times. Finally, the validity of the proposed method is shown by numerical simulations.

关键词： Multiple UAVs Cooperative guidance Intermittent communication topologies Finite time consensus Unmanned Aerial Vehicle Guidance

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Biologically inspired information integration pooling module of spiking neural networks for rolling bearing fault diagnosis

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Expert systems with Applications 2025年 286卷

作者： Shi, Mingfei Jiang, Feng Li, Yongbo Du, Lin MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China Unmanned System Research Institute Northwestern Polytechnical University Xi'an710072 China School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'an710072 China School of Aeronautics Northwestern Polytechnical University Xi'an710072 China School of Mathematics and Statics Northwestern Polytechnical University Xi'an710072 China MOE Key Laboratory for Complexity Science in Aerospace Northwestern Polytechnical University Xi'an710072 China

Rolling bearings constitute critical components in mechanical systems, and their effective fault diagnosis plays a vital role in ensuring operational safety and reliability. Despite substantial advancements in diagnostic methodologies, achieving high-precision, low-latency fault detection in large-scale rolling bearing datasets remains a persistent challenge. Artificial neural networks to spiking neural networks (ANN-to-SNN) conversion algorithms offer promising solutions for reducing computational costs and hardware adaptation barriers compared to conventional approaches. However, inherent information degradation during conversion processes has been demonstrated to significantly undermine model performance in terms of accuracy, stability, and interpretability. To overcome these limitations, we propose IIPooling, a novel Information-Integration biological neural mechanism-inspired Pooling module designed to enhance global structural feature extraction. The proposed framework incorporates three core neurobiological information processing principles: (1) promotion, (2) lateral inhibition, and (3) longitudinal inhibition, effectively simulating biological neuronal spiking patterns while optimally utilizing ANN activation characteristics. Additionally, we develop two adaptive learning mechanisms — Surrogate Gradient Adaptive Learning and Spiking Spatiotemporal Adaptive Learning — to implement negative feedback mechanism and adaptive parameter adjustment, thereby improving cross-conditional generalization capabilities. Comprehensive evaluations conducted on five bearing datasets (CWRU: DE/FE, PU, and Lab-collected: 6025/N205EW) demonstrate superior performance across four metrics (ACC, AUC, AUPRC, Mean-ACC). Our method achieves state-of-the-art results, notably attaining ACC values of 0.959 (CWRU-DE) and 0.861 (Lab-N205EW) in IIPooling-ST configurations, confirming its effectiveness for real-time, high-accuracy fault detection in complex operational environments. © 2025

关键词： Failure rate

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Towards Distributed Privacy-Preserving Prediction

Towards Distributed Privacy-Preserving Prediction

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IEEE International Conference on systems, Man and Cybernetics

作者： Lingjuan Lyu Yee Wei Law Kee Siong Ng Shibei Xue Jun Zhao Mengmeng Yang Lei Liu National University of Singapore School of Engineering University of South Australia Software Innovation Institute Australian National University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University School of Computer Science and Engineering Nanyang Technological University Singapore Unicloud Engine Technology Co. Ltd China

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

In privacy-preserving machine learning, individual parties are reluctant to share their sensitive training data due to privacy concerns. Even the trained model parameters or prediction can pose serious privacy leakage. To address these problems, we demonstrate a generally applicable Distributed Privacy-Preserving Prediction (DPPP) framework, in which instead of sharing more sensitive data or model parameters, an untrusted aggregator combines only multiple models' predictions under provable privacy guarantee. Our framework integrates two main techniques to guarantee individual privacy. First, we introduce the improved Binomial Mechanism and Discrete Gaussian Mechanism to achieve distributed differential privacy. Second, we utilize homomorphic encryption to ensure that the aggregator learns nothing but the noisy aggregated prediction. Experimental results demonstrate that our framework has comparable performance to the non-private frameworks and delivers better results than the local differentially private framework and standalone framework.

关键词： Privacy Training data Machine learning Predictive models Data models Encryption Noise measurement

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