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Inexact proximal gradient algorithm with random reshuffling for nonsmooth optimization

Science China(information Sciences) 2025年第1期68卷 219-237页

作者： Xia JIANG Yanyan FANG Xianlin ZENG Jian SUN Jie CHEN National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center School of Electronic and Information Engineering Tongji University

Proximal gradient algorithms are popularly implemented to achieve convex optimization with nonsmooth regularization. Obtaining the exact solution of the proximal operator for nonsmooth regularization is challenging because errors exist in the computation of the gradient; consequently, the design and application of inexact proximal gradient algorithms have attracted considerable attention from researchers. This paper proposes computationally efficient basic and inexact proximal gradient descent algorithms with random reshuffling. The proposed stochastic algorithms take randomly reshuffled data to perform successive gradient descents and implement only one proximal operator after all data pass through. We prove the convergence results of the proposed proximal gradient algorithms under the sampling-without-replacement reshuffling *** computational errors exist in gradients and proximal operations, the proposed inexact proximal gradient algorithms can converge to an optimal solution neighborhood. Finally, we apply the proposed algorithms to compressed sensing and compare their efficiency with some popular algorithms.

关键词： proximal operator random reshuffling inexact computation compressed sensing nonsmooth optimization

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Artificial Intelligence Planning of Failure Recovery Strategies in Discrete Manufacturing automation 19

Artificial Intelligence Planning of Failure Recovery Strateg...

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19th IEEE International Conference on automation Science and engineering, CASE 2023

作者： Lei, Yumeng Wilch, Jan Rupprecht, Bernhard Vogel-Heuser, Birgit The Institute of Automation and Information Systems Tum School of Engineering and Design Technical University of Munich Germany

ISBN: (纸本)9798350320695

As discrete manufacturing tends to be small batch and customized, automated Production systems (aPS) must be more flexible to adapt to the variety of products, which makes the aPS more complex and error-prone. To increase system efficiency and reduce downtime caused by manual intervention, strategies for automatic recovery are required. Currently, automatic recovery is fulfilled by portions of the control software that treat selected failures, which have been planned and implemented at design-time. To save engineering effort and treat unpredicted failures, recovery strategies should instead be generated automatically using established artificial intelligence planners. Consequently, this paper proposes a modularization of the functional control software into Control Primitives, from which generated strategies are composed. The same Control Primitives are the building blocks to manually implement the state machines of different operating modes of the aPS, Thus, no additional engineering effort is needed to prepare recoverability in the application development phase. In this paper, four approaches to model and implement PLC-executable Control Primitives are presented. Their viability is evaluated experimentally on a discrete manufacturing demonstrator machine by generating strategies for three use cases. © 2023 IEEE.

关键词： Artificial intelligence

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Data-driven output regulation control for constrained linear systems

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Science China(information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Machine Learning-Based Classification of Programming Logic Understanding Levels by Mouse-Tracking Heatmaps

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IEEE Access 2025年 13卷 89905-89914页

作者： Khaesawad, Attaporn Fukuchi, Yosuke Yem, Vibol Nishiuchi, Nobuyuki Tokyo Metropolitan University Graduate School of Systems Design Tokyo191-0065 Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Tsukuba305-8573 Japan

In the past decade, there has been a significant increase in the growth of the global technology employment market, primarily owing to the digital age, artificial intelligence expansion, cloud computing, and cybersecurity requirements. Consequently, the demand for IT professionals has increased. Introductory programming is a crucial early course in IT higher education as it aids in developing problem-solving skills. However, such courses tend to result in substantially high failure and dropout rates. Some studies have proposed solutions such as peer learning and personalized feedback, but challenges persist. One key assumption is that teacher support is likely to help mitigate these rates. However, with limited class time, teachers find it challenging to support all the students. This study aims to automatically assess the programming logic understanding level (PLUL) during introductory programming courses. We proposed a method for classifying PLUL through a block coding learning platform based on mouse-tracking heatmaps using machine learning techniques. We collected actual learning-task data from first-year university students and compared the performance of five machine learning models. The decision tree algorithm achieved an accuracy score of 76.00%, F1 score of 77.36%, sensitivity score of 75.93%, and specificity score of 76.09%. These findings demonstrate that our method can effectively classify students based on their PLUL of tasks on a block coding learning platform. © 2013 IEEE.

关键词： Students

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A Microcontroller Operating Strategy for (Micro-)Pitting and Temperature Increase Detection in Sensor-Integrating Gears Evaluated with Pre-recorded Sensor Data

A Microcontroller Operating Strategy for (Micro-)Pitting and...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Rupprecht, B. Vogel-Heuser, B. Hujo, D. Vicaria, A. Knoll, E. Stahl, K. Ochs, M. Brederlow, R. Institute of Automation and Information Systems TUM School of Engineering and Design Technical University of Munich Germany Institute of Machine Elements TUM School of Engineering and Design Technical University of Munich Germany TUM School of Computation Information and Technology Technical University of Munich Germany

ISBN: (纸本)9798350386097

Condition-based gear health monitoring is crucial to prevent unexpected machine downtimes. However, the lack of small-scale and cost-effective sensors that can be easily integrated on a system level hinders the implementation of condition-monitoring approaches. Damage to gears often occurs due to tooth contact, making it essential to acquire accurate data close to the gear engagement for reliable damage detection. Integrating sensors directly into gears is a promising solution for a space-neutral sensor system, but continuous data acquisition is limited by the energy and memory constraints of Microcontrollers (MCUs). This paper proposes and evaluates an operating strategy for detecting gear damage and temperature increases, featuring automated gear state detection to reduce energy consumption. Testing on a Cortex-M0+ MCU demonstrates its suitability for low-power devices. The strategy was tested using down-sampled pre-recorded acceleration data measured by external, high-performance sensors. An optimal MCU clock frequency is determined by evaluating its impact on energy consumption and execution time. The strategy’s energy consumption and execution time for different states are presented, highlighting opportunities for future optimization. © 2024 IEEE.

关键词： Microcontrollers

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Concept, configuration, and application of on-board nanogrids for use in electric vehicles

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Science China(Technological Sciences) 2024年第7期67卷 2053-2073页

作者： ZHAO Bing LI Yong WU Fang WAN JiangHu CAI JiuQing YANG HaiTao LIU Fang College of Electrical and Information Engineering Hunan UniversityChangsha 410082China Wuhan Second Ship Design and Research Institute Wuhan 430000China School of Automation Central South UniversityChangsha 410083China

Against the backdrop of increasingly serious climate change, researchers are attempting to extend macroscale carbon reduction research to smaller scales. With the rapid development and widespread application of electric vehicles(EVs), an effective approach for carbon reduction based on EVs has the potential to be developed. To coordinate and manage the EV platform in diverse application scenarios, the concept of an on-board nanogrid(OBNG), in which a nanogrid is combined with the EV, is proposed and defined, and the characteristics summarized. A configuration that includes a physical layer with the on-board hardware system;an information layer for logical control, energy management, and communication coordination;and an application layer that can cope with different working environments is proposed. A detailed introduction to the basic architecture and management mode of each layer is provided along with information concerning the relevant technologies for coordinated operation. New ideas and approaches to improve the existing performance are proposed, and finally, combined with a background of smart and low-carbon cities, major application scenarios are envisioned.

关键词： electric vehicle nanogrid energy management hybrid energy storage power electronics converter

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Investigation of Data Transmission Between Construction Machines and Attachment Tools via OPC UA Technology

Investigation of Data Transmission Between Construction Mach...

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International Conference on Construction Logistics, Equipment, and Robotics, CLEaR 2023

作者： Land, Kathrin Vogel-Heuser, Birgit Krüger, Marius Chen, Jan‐Kristof Fottner, Johannes Institute of Automation and Information Systems School of Engineering and Design Technical University of Munich Munich Germany Chair of Materials Handling Material Flow Logistics School of Engineering and Design Technical University of Munich Munich Germany

ISBN: (纸本)9783031440205

Construction sites require improved information logistics in order to obtain an efficient overview of the construction machine and attachment tools available on the construction site as well as their maintenance states. To enable data transfer to the central back office, an information technology integration of the machine and its tools is necessary. OPC UA is considered a potential solution to connect the devices and gather the information required. In this paper, a communication architecture using OPC UA is proposed to connect construction machine and attachment tools on the construction site with the back office. To evaluate the runtime performance of the communication architecture proposed, an experimental setup, which covers the communication on construction sites, is designed to measure the transmission time and data loss of the communication considering different PLC cycle times and data sizes. This paper contributes an order of magnitude for the transmission time and data loss in dependence of the performance class and cycle time of hardware devices. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data transfer

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LPL-VIO: monocular visual-inertial odometry with deep learning-based point and line features

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Neural Computing and Applications 2024年第36期36卷 23061-23075页

作者： Liu, Changxiang Yang, Qinhan Yu, Hongshan Fu, Qiang Akhtar, Naveed College of Electrical and Information Engineering School of Robotics Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University Changsha China School of Computing and Information Systems The University of Melbourne VIC Australia

Visual-inertial SLAM (VINS) has garnered substantial interest in the field of mobile robotics due to its robustness and cost-effectiveness. The incorporation of both point and line features in visual SLAM has shown significant performance improvements compared to relying solely on point features. Furthermore, learning-based features consistently outperform traditional hand-crafted features across a diverse range of tasks. Leveraging all these observations, we propose a novel deep learning technique, termed learning-based point and line visual-inertial odometry (LPL-VIO), which is aimed to enhance robustness and performance of traditional systems. LPL-VIO takes a 2-stage approach, including a deep learning front-end and a traditional nonlinear optimization back-end. In the first stage (front-end), we employ proposed networks for points and lines to extract and track deep learning-based point and line features in visual images, while implementing IMU preintegration. In the second stage (back-end), we adopt a sliding window strategy to tightly couple point and line re-projection errors with IMU preintegration residuals. These residuals are optimized using bundle adjustment for precise global pose estimation. Extensive experiments are conducted on both public EuRoC datasets and our own real-world dataset collected in challenging outdoor environments. Qualitative and quantitative results show that our method exhibits strong competitiveness compared with the existing point–line techniques, and outperforms the popular VINS-Mono. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： SLAM robotics

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Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 40-53页

作者： Qinglai Wei Shanshan Jiao Qi Dong Fei-Yue Wang IEEE the Institute of Systems Engineering Macau University of Science and Technology the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences the School of Artificial Intelligence University of Chinese Academy of Sciences China Academy of Electronics and Information Technology the State Key Laboratory of Multimodal Artificial Intelligence Systems the School of Artificial Intelligence University of Chinese Academy of Sciences

This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.

关键词： Adaptive dynamic programming (ADP) critic neural network (NN) event-triggered control optimal consensus control robust control

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Nanodiamond/Ti_(3)C_(2) MXene-coated quartz crystal microbalance humidity sensor with high sensitivity and high quality factor

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Rare Metals 2024年第6期43卷 2719-2729页

作者： Yao Yao Qiao Chen Yan-Qi Li Xian-He Huang Wei-Wei Ling Zhe-MiaoXie Jia-QiWang Chang-Ming Chen College of Communication Engineering Chengdu University of Information TechnologyChengdu 610225China School of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Advanced Micro-/Nano-Devices Lab Department of Systems Design EngineeringUniversity of WaterlooWaterlooON N2L 3GlCanada

To address the challenge of achieving both high sensitivity and a high quality factor in quartz crystal microbalance(QCM)humidity sensors,a nanodiamond(ND)/Ti_(3)C_(2)MXene composite-coated QCM humidity sensor was *** material characteristics of ND,Ti_(3)C_(2)MXene,and ND/Ti_(3)C_(2)MXene composite were analyzed by transmission electron microscopy(TEM)and Fourier transform infrared(FTIR)*** experimental results demonstrated that the hydrophilic ND nanoparticles coated on Ti_(3)C_(2) MXene nanosheet prevented the self-stacking of Ti_(3)C_(2)MXene and enhanced the sensitivity of Ti_(3)C_(2) MXene-based QCM humidity ***,the high mechanical modulus of Ti_(3)C_(2) MXene material helped ND/Ti_(3)C_(2)MXene composite-coated QCM humidity sensor to achieve a high quality factor(>20,000).ND/Ti_(3)C_(2)MXene compositecoated QCM humidity sensor exhibited a sensitivity of 82.45 Hz/%RH,a humidity hysteresis of 1.1%RH,fast response/recovery times,acceptable repeatability,and good stability from 11.3%RH to 97.3%*** response mechanism of ND/Ti_(3)C_(2) MXene composite-coated QCM humidity sensor was analyzed in combination with a bi-exponential kinetic adsorption ***,the potential application of ND/Ti_(3)C_(2)MXene composite-coated QCM humidity sensor was demonstrated through its frequency response to wooden blocks with different moisture contents.

关键词： Humidity sensor Quartz crystal microbalance Nanodiamond Ti_(3)C_(2)MXene High quality factor

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