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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Li, Jialong Guo, XiWang Wang, Jiacun Qin, ShuJin Qi, Liang Kang, Qi Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Wes Long Branch Computer Science and Software Eng. NJ United States Shangqiu Normal University Economics and Management Shangqiu China Shandong University of Science and Technology Computer Science and Technology Qingdao China New Jersey Institute of Technology Electrical and Computer Engineering Newark United States

ISBN: (纸本)9798350376739

There is increasing attention on remanufacturing, with the primary focus in the industry on recovering reusable products to generate profit. In the process of optimizing remanufacturing, addressing the balance issue in the operation of the disassembly line is crucial. Therefore, this study proposes the use of an improved Dingo Optimization Algorithm (IDOA) and designs a mathematical model for human-robot collaboration to explore how to achieve higher profits under these conditions. Finally, the improved IDOA is experimentally compared with the commercial optimization solver CPLEX and another intelligent optimization method - the Battle Royale Optimization (BRO). The results demonstrate that this method offers high quality and efficiency. © 2024 IEEE.

关键词： Microrobots

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Design of a Mechatronic Endoskeleton Robot for Inspection Tasks: Model Reference Adaptive control (MRAC) for Serpentine Locomotion with Stability Analysis 17

Design of a Mechatronic Endoskeleton Robot for Inspection Ta...

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17th International Conference on Developments in eSystems engineering, DeSE 2024

作者： Al Mhdawi, Ammar K. Wright, Nick Younis, Mohammed I. Humaidi, Amjad J. School of Engineering and Sustainable Development De Montfort University LeicesterLE19BH United Kingdom Department of Electrical and Electronic Engineering Newcastle University Newcastle United Kingdom Department of Computer Engineering University of Baghdad Iraq Department of Control and Systems Engineering University of Technology Baghdad Iraq

ISBN: (纸本)9798350368697

An advantage of bio-inspired robots is the versatility of their locomotion on a wide range of terrains that conventional robots are not able to traverse. The snake-like robot, which is a mechanism designed to move in the manner of a biological snake, is an example of a bio-inspired platform. This paper aims to implement and validate, using real and simulation tests on flat terrain, a snake-like endoskeleton robot that permits serpentine movement with adaptive control capabilities. The prototype mechatronic robot was comprised of eleven segments that were 3D printed sequentially. A simulation using Matlab’s Multibody Mechanics tool determines the necessary torques for each motor. In this simulation, a parameterized virtual model of the robot is created, where rectilinear gaits are programmed. In accordance with simulation and experimental results, the robot undertakes different times to reach the goal trajectory or end points depending on the frequency, angular position, and wave length (duty cycle). As a result, there is a high degree of similarity between the simulation tests and those conducted with the prototype endoskeleton. Furthermore, the robot is equipped with machine vision capabilities that allow it to detect faults within oil and gas pipes for the purpose of inspection and maintenance. Furthermore, a Model Reference Adaptive control (MRAC) method based on Lyapunov stability analysis and MIT rules is proposed. The theoretical analysis and numerical simulation show that the designed trajectory tracking control law can make the multi-joint snake-like robot track the trajectory of the front joint when the robot encounters disturbances and stabilize the angular position and velocity of the first two head joints when disturbances occur. © 2024 IEEE.

关键词： Model reference adaptive control

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Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction Systems in High-Speed Trains

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Chinese Journal of Electronics 2023年第5期32卷 982-991页

作者： CHENG Chao WANG Weijun MENG Xiangxi SHAO Haidong CHEN Hongtian Department of Computer Science and Technology Changchun University of Technology Department of Mathematics and Statistics Changchun University of Technology Institute of System Research China Industrial Control Systems Cyber Emergency Response Team Department of Mechanical and Vehicle Engineering Hunan University Department of Chemical and Materials Engineering University of Alberta

Fault detection(FD) for traction systems is one of the active topics in the railway and academia because it is the initial step for the running reliability and safety of high-speed trains. Heterogeneity of data and complexity of systems have brought new challenges to the traditional FD methods. For addressing these challenges, this paper designs an FD algorithm based on the improved unscented Kalman filter(UKF) with consideration of performance degradation. It is derived by incorporating a degradation process into the state-space *** network topology of traction systems is taken into consideration for improving the performance of state estimation. We first obtain the mixture distribution by the mixture of sigma points in UKF. Then, the Lévy process with jump points is introduced to construct the degradation model. Finally, the moving average interstate standard deviation(MAISD) is designed for detecting *** the proposed methods via a traction systems in a certain type of trains obtains satisfactory results.

关键词： Degradation Network topology Fault detection Rail transportation State-space methods Safety Kalman filters

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Research on SDN traffic anomaly detection technology based on knowledge graph 5

Research on SDN traffic anomaly detection technology based o...

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5th International Conference on Artificial Intelligence and computer Science, AICS 2023

作者： Li, Suyang Bai, Xiaojun Wang, Shenhang School of Computer Science and Engineering Xi’an Technological University Shaanxi Xi’an710021 China Beijing Aerospace Automatic Control Institution Beijing100076 China

ISBN: (纸本)9781510668621

SDN (Software Defined Networking) is a novel network architecture that allows for flexible configuration and centralized control of resources. However, it also presents new fault problems, particularly in high data volumes and complex topologies where traditional anomaly detection algorithms often need to be revised. To address this issue, we propose a knowledge graph-based approach to SDN fault detection. By leveraging the interpretability and expressiveness of knowledge graphs and the SDN controller’s global information, we construct and continuously update a knowledge graph that enables real-time monitoring and analysis of the network state. Finally, we detect and diagnose the abnormal conditions in the network through graph inference. The experimental results indicate that the knowledge graph-based SDN fault detection algorithm demonstrates high accuracy and efficiency, effectively enhancing SDN networks’ operational stability and security. © 2023 SPIE.

关键词： Anomaly detection

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An LSTM-PSO-Based Predictive Strategy and Its Application in the Main Steam Temperature control in Power Plants 2

An LSTM-PSO-Based Predictive Strategy and Its Application in...

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2023 2nd International Conference on Power System and Power engineering, PSPE 2023

作者： Jin, Fei Hao, Xiaoguang Yin, Zhe Yang, Chunlai Liu, Xuelai Shi, Yijun State Grid Hebei Energy Technology Service Co. Ltd Shijiazhuang050021 China School of Control and Computer Engineering Beijing102206 China

We proposed an LSTM-PSO predictive controller strategy to overcome the large delay and strong disturbance during main steam temperature control. First, the long short-term memory (LSTM) network model was developed to forecast the future trend of mainstream temperature, and the deviation between the model output and the expected value after feedback correction was minimized by the particle swarm optimization (PSO) algorithm. Then, the LSTM-PSO predictive controller was taken as the primary controller to maintain the steam temperature of the coal-fired boiler. A comparative simulation with conventional PID cascade control and dynamic matrix controller strategies was given, and the test calculations indicate that the adjustment time was shortened and the overshoot was reduced. Finally, the LSTM - PSO predictive control strategy was deployed into the actual boiler operation process of a 300 MW coal-fired power plant, within 0.5 °C steady-state error and 2 °C dynamic error. © Published under licence by IOP Publishing Ltd.

关键词： controllers

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Lightweight Security Protection System Architecture for Digital Grid Mobile Application Platform 2

Lightweight Security Protection System Architecture for Digi...

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2nd International Conference on Green Communication, Network, and Internet of Things, CNIoT 2022

作者： Ren, Jiyuan Liu, Fuyang Song, Yang Wang, Zhe Yin, Lu Wang, Jing Dispatching and Control Center Northeast Branch of State Grid Corporation of China Shenyang China School of Computer Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9781510662940

The risk of data leakage and security vulnerabilities exist in digital grid mobile application platforms such as "i State Grid". To address this problem, an application security plug-in for digital grid smart terminals is designed. A lightweight mobile application security protection system architecture is proposed to prevent user data from being damaged and leaked. The system architecture mainly contains three aspects: static environment assessment of mobile applications, dynamic detection of malicious applications, and mobile application risk assessment. That also reduces the security risk from external factors such as the Internet, and effectively ensures the safe and stable operation of the "i State Grid" system. © 2023 SPIE.

关键词： Risk assessment

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Real-time Sleep Prediction Algorithm using Commercial Off the Shelf Wearable Devices 9

Real-time Sleep Prediction Algorithm using Commercial Off th...

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9th IEEE Smart World Congress, SWC 2023

作者： Pugliese, Luigi Violante, Massimo Groppo, Riccardo Politecnico di Torino Dept. of Control and Computer Engineering Turin Italy Sleep Advice Technologies S.r.l. Turin Italy

ISBN: (纸本)9798350319804

As reported by the American National Highway Traffic Safety Administration (NHTSA), sleep while driving is one of the most influential factors in fatal vehicle crashes, along with excessive vehicle speed and alcohol consumption. Physiologically speaking, driving for more than two hours in a nocturnal environment produces a driving impairment like a blood alcohol concentration of 0.05%. In this work, we present an innovative and patented sleep prediction method based on the analysis of the Autonomic Nervous System (ANS) (and its subsystems) that monitors the actions happening during the transition from awake to sleep onset. The prediction method processes the Heart Rate (HR) and the Heart Rate Variability (HRV) as collected by a wearable device on the subject wrist. Using a sliding window approach that operates on 20 seconds of samples (acquired at 1 Hz), the trend of the variance of HR and HRV is used to classify the subject condition according to a reduced Karolinska Sleepiness Scale (rKSS) that comprises five stages: Calibration, Awake, Low Drowsiness level, Medium Drowsiness level, High Drowsiness level. The prediction method has been validated experimentally using a set of recordings acquired in a realistic environment (AVL dynamic car simulator, in Graz (AT)). During the experiments, 15 subjects performed several rounds of the Maintenance Wakefulness Test (MWT). Each subject was equipped with a wearable device and apolysomnography medical equipment to gather both the data processed by the proposed approach, and the data set that constituted the ground truth under the supervision of a sleep expert medical doctor. A further experimental section has been conducted, involving the Italian truck company Chrono Express. 15 different drivers have utilized the built-up system for more than 13000 km. The proposed method is sensor agnostic, as it has been proven through preliminary activities with contactless Radio Frequency (RF) sensors. The output produced by the propos

关键词： Drowsiness Heart Rate Heart Rate Variability IOT Physiological data Real-time Rule-based algorithm Sleep

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Computationally Efficient Core Losses Calculation and Thermal Evaluation Using the VBR-Based Finite Element Model of Induction Motors

Computationally Efficient Core Losses Calculation and Therma...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Valipoor, Zahra Koti, Hossein Nejadi Demerdash, Nabeel A. O. Marquette University Electrical and Computer Engineering Department Milwaukee United States Rockwell Automation Inc. Motion Control Team Mequon United States

ISBN: (纸本)9798350316445

Accuracy of the simulation results obtained from the FEA analysis of electric motors is highly dependent on the quality of the motor performance metrics such as motor steady state temperatures and losses. In addition such FEA analysis is typically computationally burdensome and demanding. Improving the computational burden and accuracy of core losses calculation and thermal evaluation in Time-Stepping Finite Element (TS-FE) models of induction motors is addressed in this paper. The Virtual Blocked Rotor (VBR)-based Time-Stepping Finite Element (TS-FE) technique is utilized to mitigate the numerical transient response of the induction motor FE model. The motor core losses have been calculated through the harmonic based core loss calculation that assumes variable loss coefficients as a function of magnetic flux density. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components. © 2023 IEEE.

关键词： Core Losses Induction Motor Temperature Thermal Calibration VBR-based FEA

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Improved Proximal Policy Optimization Algorithm for Multi-objective Disassembly Line Balancing Considering Hazardous Tasks 21

Improved Proximal Policy Optimization Algorithm for Multi-ob...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Guo, Zeyu Guo, Xiwang Wang, Jiacun Qin, Shujin Qi, Liang Kang, Qi Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. Wes Long BranchNJ United States Shangqiu Normal University Economics and Management Shangqiu China Shandong Technology University Computer Science Department Qingdao China New Jersey Institute of Technology Electrical and Computer Engineering Newark United States

ISBN: (纸本)9798350365221

As disassembly lines evolve, keeping workers safe from all potential dangers has become paramount. This work proposes an improved approach, Proximal Policy Optimization for Disassembly Line(PPO-DL), to address Multi-objective Dis-assembly Line Balancing Problem(MDLBP) that integrates task switching time and hazardous tasks. The MDLBP model aims to optimize disassembly net profit, balance workstation utilization, and mitigate penalties from hazardous tasks. The proposed PPO-DL modifies the action space of PPO to accommodate MD LBP characteristics, ensuring efficient learning by restricting actions to valid ranges through action masking. Comparative experiments with PPO, Q-learning, and A2C demonstrate PPO-DL's superiority in finding near-optimal solutions across various scenarios. © 2024 IEEE.

关键词： Assembly machines

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