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Machine learning-based prediction of microstructure and mechanical properties for 12Cr2Mo1V large cylindrical forgings

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Materials Today Communications 2025年 47卷

作者： Wang, Xingfu Mao, Feng Li, Xin Miao, Kunlin Shi, Ruxing Lin, Yichou Chen, Chong Wang, Changji Yu, Hua Wei, Shizhong School of Materials Science and Engineering Henan University of Science and Technology Luoyang471023 China Longmen Laboratory Luoyang471000 China National Joint Engineering Research Center for Abrasion Control and Molding of Metal Materials Henan University of Science and Technology Luoyang471003 China College of Mechanical and Electrical Engineering Zhengzhou University of Light Industry Zhengzhou450002 China School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou450002 China CITIC Heavy Industries Co. Ltd. Henan Luoyang471039 China

This study addresses the challenges of strong empirical dependence, high trial-and-error costs, and technical difficulties in mechanical property prediction for 12Cr2Mo1V large cylindrical forgings by proposing a machine learning-based performance prediction methodology. Industrial data from hot forging production lines were collected, preprocessed, and utilized to comparatively analyze the predictive performance of various computational models. Results demonstrate that Support Vector Machine (SVM) exhibits superior performance in predicting critical indicators including grain size, normal-temperature tensile strength, and high-temperature tensile strength. Experimental validation confirmed strong consistency between model predictions and empirical measurements, verifying the methodology's practical applicability. Integration with the Mean Impact Value (MIV) algorithm elucidated the causal relationships between process parameters and the mechanical properties of large cylindrical forgings. This research establishes a data-driven predictive framework for optimizing the forging process of 12Cr2Mo1V steel, effectively reducing trial-and-error expenses while enhancing quality consistency in large pressure vessel forgings, with significant implications for high-performance material design and manufacturing. © 2025 Elsevier Ltd

关键词： Tensile strength

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Privacy-Aware Joint DNN Model Deployment and Partition Optimization for Delay-Efficient Collaborative Edge Inference

arXiv

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arXiv 2025年

作者： Cheng, Zhipeng Xia, Xiaoyu Wang, Hong Liwang, Minghui Chen, Ning Fan, Xuwei Wang, Xianbin School of Future Science and Engineering Soochow University Suzhou215006 China School of Computing Technologies RMIT University MelbourneVIC Australia Department of Control Science and Engineering The National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai201804 China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Tongji University Shanghai201804 China Qingdao China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China Department of Electrical and Computer Engineering Western University ON Canada

Edge inference (EI) is a key solution to address the growing challenges of delayed response times, limited scalability, and privacy concerns in cloud-based Deep Neural Network (DNN) inference. However, deploying DNN models on resource-constrained edge devices faces more severe challenges, such as model storage limitations, dynamic service requests, and privacy risks. This paper proposes a novel framework for privacy-aware joint DNN model deployment and partition optimization to minimize long-term average inference delay under resource and privacy constraints. Specifically, the problem is formulated as a complex optimization problem considering model deployment, user-server association, and model partition strategies. To handle the NP-hardness and future uncertainties, a Lyapunov-based approach is introduced to transform the long-term optimization into a single-time-slot problem, ensuring system performance. Additionally, a coalition formation game model is proposed for edge server association, and a greedy-based algorithm is developed for model deployment within each coalition to efficiently solve the problem. Extensive simulations show that the proposed algorithms effectively reduce inference delay while satisfying privacy constraints, outperforming baseline approaches in various scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Differential privacy

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Robust Reinforcement Learning for Stochastic Linear Quadratic control with Multiplicative Noise ⁎

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IFAC-PapersOnLine 2021年第7期54卷 240-243页

作者： Bo Pang Zhong-Ping Jiang Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering New York University Six Metrotech Center Brooklyn NY 11201 USA

This paper studies the robustness of reinforcement learning for discrete-time linear stochastic systems with multiplicative noise evolving in continuous state and action spaces. As one of the popular methods in reinforcement learning, the robustness of policy iteration is a longstanding open issue for the stochastic linear quadratic regulator (LQR) problem with multiplicative noise. A solution in the spirit of small-disturbance input-to-state stability is given, guaranteeing that the solutions of the policy iteration algorithm are bounded and enter a small neighborhood of the optimal solution, whenever the error in each iteration is bounded and small. In addition, a novel off-policy multiple-trajectory optimistic least-squares policy iteration algorithm is proposed, to learn a near-optimal solution of the stochastic LQR problem directly from online input/state data, without explicitly identifying the system matrices. The efficacy of the proposed algorithm is supported by rigorous convergence analysis and numerical results on a second-order example.

关键词： Reinforcement learning control Stochastic optimal control problems Data-based control Robustness analysis Input-to-state stability

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Design and Application of a One-Stop Mobile Application Sharing Platform for Steel Enterprises

Design and Application of a One-Stop Mobile Application Shar...

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Chinese control Conference (CCC)

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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An Exoskeleton BCI System for Stroke Rehabilitation Using Multi-modality Training Mode

An Exoskeleton BCI System for Stroke Rehabilitation Using Mu...

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2023 International Automatic control Conference, CACS 2023

作者： Su, Kai-Hsiang Chen, Chiao-Hsin Chen, Chia-Hsin Zhang, Yong-Liang Ko, Li-Wei National Yang Ming Chiao Tung University Former National Chiao Tung University Institute of Biological Science and Technology Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Former National Chiao Tung University Institute of Molecular Medicine and Bioengineering Hsinchu30010 Taiwan Medical University Chung-Ho Memorial Hospital Rehabilitation Department of Kaohsiung Taiwan College of Biological Science and Technology Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Former National Chiao Tung University Institute of Electrical and Control Engineering Hsinchu30010 Taiwan Brain Research Center Department of Electrical and Computer Engineering Hsinchu30010 Taiwan

ISBN: (纸本)9798350306354

With the advent of the global aging era, the impact of stroke on humans is continuously increasing. Therefore, new therapeutic approaches to enhance patient recovery are receiving growing attention. Stroke is a severe neurological disorder that causes brain damage, requiring extended periods of rehabilitation for patients to return to normal life. Currently, common clinical methods largely rely on traditional passive limb rehabilitation, primarily targeting peripheral nerve training. Nowadays, an increasing number of people are recognizing the importance of post-stroke neuroplasticity. This study aims to activate patients' central nervous system and proposes a brain-machine interface (BCI) exoskeleton system based on human cognition. By designing three cognitive brainwave training models, including an attention-based standing-up model detecting θ-band power decrease, a relaxation-based sitting-down model detecting α-band power increase, and a walking model detecting MRCP, patients can actively control lower limb exoskeleton movement using *** study provides cross-validation accuracy through both normal subjects and stroke patients, with accuracies of 87.13±9.38 and 80.83±9.68, respectively. Envisioning a rehabilitation system guided by human cognition, our team has developed an intuitive BCI exoskeleton system. © 2023 IEEE.

关键词： Brain

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Linear Quadratic Guidance Law for Joint Motion Planning of a Pursuer-Turret Assembly

arXiv

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arXiv 2024年

作者： Jha, Bhargav Bopardikar, Shaunak D. Von Moll, Alexander Casbeer, David Michigan State University East LansingMI48864 United States Air Force Research Laboratory WPAFB OH45433 United States Department of Electrical and Computer Engineering Michigan State University United States Control Science Center 2210 8th St.

This paper presents joint motion planning of a vehicle with an attachedrotating turret. The turret has a limited range as well as the field of *** objective is capture a maneuvering target such that at the terminal time itis withing the field-of-view and range limits. Catering to it, we present aminimum effort guidance law that commensurate for the turn rate abilities ofthe vehicle and the turret. The guidance law is obtained using linearizationabout the collision triangle and admits an analytical solution. Simulationresults are presented to exemplify the cooperation between the turret and thevehicle. © 2024, CC BY.

关键词： Motion planning

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Predictor-Based Constrained Fixed-Time Sliding Mode control of Multi-Uav Formation Flight

SSRN

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SSRN 2024年

作者： Khodaverdian, Maria Hajshirmohamadi, Shahram Hakobyan, Aleksandr Ijaz, Salman Center for Scientific Innovation and Education Aerial Robotics Laboratory of National Polytechnic University of Armenia Yerevan Armenia Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Key Laboratory of More Electric Aircraft and Control System Lab University of Nottingham Ningbo China

In this work, a predictor-based fixed-time sliding mode control is designed to tackle the problem of achieving precise trajectory tracking control of multiple unmanned aerial vehicles formation flight. The proposed approach simultaneously addresses various practical requirements, such as optimality, constraints, fixed-time convergence, external interferences, and computational ***, a constrained performance index is constructed based on the prediction of the fixed-time sliding surface, the reaching law, and the control input. Secondly, optimal control input is calculated by solving the constrained quadratic optimization problem. An outstanding feature of this study is the theoretical guarantee of closed-loop system stability in the presence of external disturbances and ***, the comparative evaluation with sliding mode predictive control law and fixed-time sliding mode control methods demonstrates that the proposed approach achieves a straightforward control method with improved performance and acceptable accuracy. Finally, a test is conducted to demonstrate the algorithm's potential for hardware implementation by employing Hardware-in-the-Loop (HIL) test. © 2024, The Authors. All rights reserved.

关键词： Sliding mode control

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Global Finite Time Stabilization of SISO Hurwitz Linear Systems Subject to Actuator Saturation: The Case of Real Eigenvalues

Global Finite Time Stabilization of SISO Hurwitz Linear Syst...

引用

American control Conference (ACC)

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A.

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper considers the global finite time stabilization of linear systems subject to actuator saturation. We show that a controllable SISO system whose eigenvalues are real and negative can be globally stabilized in finite time by a homogeneous feedback law. To obviate numerical issues, this homogeneous feedback law is implemented by discretizing a compact set. Numerical simulation validates the effectiveness of the proposed approach.

关键词： Linear systems Actuators Numerical simulation control systems Eigenvalues and eigenfunctions

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Stealthy Attacks on Sampled-Data control and Encryption-Based Countermeasures

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IEEE Transactions on Automatic control 2025年

作者： Shang, Jun Li, Yuzhe Chen, Tongwen Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

This paper investigates stealthy attacks on sampled-data control systems, where a continuous process is sampled periodically, and the resultant discrete output and control signals are transmitted through dual channels in wireless communication networks. Acknowledging the vulnerability of these transmitted data to cyber threats, we analyze two types of stealthy attacks that compromise either one or both channels. We explicitly present the necessary and sufficient conditions for the existence of stealthy single-channel attacks. To mitigate these security risks, we implement encryption-based countermeasures, including linear time-invariant and periodic encryption methods. We detail sufficient conditions under which these encryption strategies effectively thwart single- and dual-channel stealthy attacks. The effectiveness of these approaches and the theoretical findings are demonstrated through numerical simulations. © 1963-2012 IEEE.

关键词： Cyber attacks

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Homodyne measurement with a Schrödinger cat state as a local oscillator

引用

Physical Review A 2022年第6期106卷 063706-063706页

作者： Joshua Combes Austin P. Lund Department of Electrical Computer and Energy Engineering University of Colorado Boulder Colorado 80309 USA Dahlem Center for Complex Quantum Systems Freie Universität Berlin 14195 Berlin Germany Centre for Quantum Computation and Communications Technology School of Mathematics and Physics The University of Queensland St Lucia QLD Australia

Homodyne measurements are a widely used quantum measurement. Using a coherent state of large amplitude as the local oscillator, it can be shown that the quantum homodyne measurement limits to a field quadrature measurement. In this work, we give an example of a general idea: injecting nonclassical states as a local oscillator can lead to nonclassical measurements. Specifically, we consider injecting a superposition of coherent states, a Schrödinger cat state, as a local oscillator. We derive the Kraus operators and the positive operator-valued measure in this situation.

关键词： Optics & lasers Quantum engineering Quantum optics Quantum sensing

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