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Intelligent optimisation scheduling of raw material area in sausage production line

International Journal of Simulation and Process Modelling 2023年第4期20卷 239-254页

作者： Han, Zhonghua Guan, Mingpeng Liu, Hangyu Chang, Daliang Sun, Liangliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110017 China School of Control Engineering Northeastern University at Qinhuangdao Hebei Qinhuangdao066099 China

The production process in the raw material area of the sausage production line needs to be further optimised to improve production efficiency and reduce the waiting time for suctioning of emulsifying fillings. In this study, we propose an improved Q-learning method for scheduling in raw material area (RMSPS-IQL). To overcome the problem of low learning efficiency caused by multi-operation and multi-tasking in the production line scheduling process, a priority stranding probability is added to the action selection method based on the epsilon-greedy strategy. In addition, to determine the execution time of the action during continuous working, a stranding action starting control method based on the probability of filling deterioration was designed. Comparative analysis of the results of multiple simulation schemes suggested that the RMSPS-IQL effectively reduces the waiting time for suctioning fillings from emulsifying pot, and improves the productivity of the production line. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Filling

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Multi‐objective particle swarm optimisation of complex product change plan considering service performance

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1058-1076页

作者： Ruizhao Zheng Yong Zhang Xiaoyan Sun Faguang Wang Lei Yang Chen Peng Yulong Wang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina Shenzhen Skyworth RGB Electronics Co. LtdShenzhenChina School of Mechatronic Engineering and Automation Shanghai UniversityShanghaiChina

Design change is an inevitable part of the product development *** study proposes an improved binary multi‐objective PSO algorithm guided by problem char-acteristics(P‐BMOPSO)to solve the optimisation problem of complex product change plan considering service ***,a complex product multi‐layer network with service performance is established for the first time to reveal the impact of change effect propagation on the product service ***,the concept of service performance impact(SPI)is defined by decoupling the impact of strongly associated nodes on the service performance in the process of change affect ***,a triple‐objective selection model of change nodes is established,which includes the three indicators:SPI degree,change cost,and change ***,an integer multi‐objective particle swarm optimisation algorithm guided by problem characteristics is developed to solve the model *** results on the design change problem of a certain type of Skyworth TV verify the effectiveness of the established optimisation model and the proposed P‐BMOPSO algorithm.

关键词： multi‐objective particle swarm optimization product change service performance

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Design of 2 DOF Fuzzy control System for Fuel Cell Systems

Design of 2 DOF Fuzzy Control System for Fuel Cell Systems

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Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

作者： Kendir, Fatih Kumbasar, Tufan Control and Automation Engineering Department Istanbul Technical University İstanbul Turkey AVL Research and Engineering İstanbul Turkey

ISBN: (纸本)9783031397769

Fuel Cell Systems (FCSs) are a promising energy source for various applications due to their high efficiency and low environmental impact. However, the commercialization of FCSs has been hindered by their limited lifespan, which is largely affected by cell degradation. To address this issue, we propose a 2 DOF fuzzy control system that is capable to maximize the net stack output power while considering cell degradation. The proposed control system is composed of a data-driven Reference Generator (RG), a data-driven Feedforward controller (FFC), and a feedback PI controller which are designed to regulate the Oxygen Excess Ratio (OER) to achieve maximum net power output. To handle the dominant nonlinearity, we learn and deploy Fuzzy Models (FMs) as the RG and FFC. In this context, we analyzed the stack current-OER relationship at optimal stack temperature and learned the nonlinear characteristic with FMs. Then, the PI controller is tuned to track the generated reference to maximize the net stack power for different stack currents. To analyze the impact of improvements on cell lifetime, we developed a degradation model based on electrochemical impedance spectroscopy. The results show that the fuzzy control system can maximize the net stack output power while simultaneously prolonging fuel cell life as a result of the high-performing OER control loop. We believe that the proposed 2 DOF fuzzy control system is a step towards the commercialization of fuel cells and enables their widespread adoption as a sustainable energy source for various applications. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuel cells

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An adaptive large neighborhood search for the multi-point dynamic aggregation problem

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control Theory and Technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collaborate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collaboration

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Guided Transformative GAN: Joint Face Image Super-Resolution and Frontalization 10

Guided Transformative GAN: Joint Face Image Super-Resolution...

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10th International Conference on Systems and Informatics, ICSAI 2024

作者： Mu, Minghao Wang, Wei Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9798331510138

Joint face super-resolution and frontalization of non-frontal low-resolution faces is of significant importance for many face analysis applications. However, at the same time, it is a challenging task. In this paper, a novel Guided Transformative Generative Adversarial Network (GT-GAN) is proposed to address the challenge of generating frontal high-resolution face images from non-frontal low-resolution face images. Existing methods usually treat super-resolution and frontalization as two separate tasks, leading to unsatisfactory processing results. GTG AN innovatively achieves both goals within a unified frame-work. Specifically, we propose Profile Attention Guidance (PAG) to generate landmark heatmaps that provide a priori pose information to the generative network and direct its attention to critical facial regions. In addition, an Attention Fusion Transformation Module (AFTM) is proposed to significantly improve the hallucination performance of the network by utilizing the attention mechanism and STNs, combined with sequential feature enhancement strategies. The experimental results show that GT-GAN exhibits superior performance in the joint face super-resolution and frontalization task on the public face dataset Multi-PIE, which provides new ideas and references for this challenging topic. © 2024 IEEE.

关键词： Generative adversarial networks

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Industrial Gearbox Fault Diagnosis Based on Vision Transformer and Infrared Thermal Imaging

Industrial Gearbox Fault Diagnosis Based on Vision Transform...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Li, Yan Cao, Xunqi Wang, Haoyu Yu, Kun Zhang, Yongchao School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

ISBN: (纸本)9783031734069

Infrared thermal imaging technology measures the intensity of external radiation emitted by objects, producing thermal images that depict their outlines and surface temperature distribution. This method holds tremendous potential for monitoring the health status of gearboxes, offering a highly promising approach to ensure their optimal performance and longevity. By utilizing the rich features of thermal images, it is possible to distinguish the health status of gearboxes from a new technological perspective. However, the traditional infrared thermal imaging technology method based on Convolutional Neural Network (CNN) has limitations in capturing the overall features and contextual relationships of images. Vision Transformer (ViT) network uses self-attention mechanism to fully explore the correlation within features, which can effectively represent the global information of high-dimensional features. Therefore, this article proposes a ViT network method for gearbox fault diagnosis by using infrared thermal imaging. The effectiveness of this method is verified by using experimental data from an industrial gearbox. Compared with other comparison methods, the proposed method exhibits better diagnostic results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Urban Traffic control Meets Decision Recommendation System:A Survey and Perspective

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2043-2058页

作者： Qingyuan Ji Xiaoyue Wen Junchen Jin Yongdong Zhu Yisheng Lv Zhejiang Lab Hangzhou 311121China College of Engineering and Architecture Zhejiang UniversityHangzhou 310013China College of Electrical Engineering Zhejiang UniversityHangzhou 310013China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation *** approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and ***,this process is cumbersome,labor-intensive,and cannot be applied on a large network *** studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and *** a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been *** this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.

关键词： Recommendation system traffic control traffic perception traffic prediction

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Time-varying formation-containment control for heterogeneous multi-agent systems with communication and output delays via observer-based feedback protocol

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IEEE Transactions on automation Science and engineering 2025年 22卷 15435-15448页

作者： Yang, Yi He, Yong China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

In this article, the time-varying formation-containment control problem of heterogeneous multi-agent systems (MASs) with an observer-based state feedback protocol is studied, where both communication delays and output delays are taken into consideration. By introducing an augmented Lyapunov-Krasovskii functionals (LKFs) candidate and employing less conservative methods to estimate its derivative, an improved quasi-formation-containment criterion is derived. On this basis, some observers and controllers are designed to allow for a larger maximum upper bound (MUB) of time delays on the premise of guaranteeing the fulfillment of the time-varying formation of leaders and the bounded convergence of followers. The estimation of the MUB determines the allowable delay range for system stability under the designed observers and controllers. Moreover, a distributed algorithm is developed to calculate the MUB of time delays, the observer gains, and the controller gains. Finally, two simulation experiments are implemented to demonstrate the obtained results, which verify the superiority and practicability of the criterion and algorithm. © 2004-2012 IEEE.

关键词： State feedback

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RSD-Diff: Boundary-Frequency Feature-Enhanced Rail Surface Defect Inspection with Diffusion-Based Transformer Decoder 10

RSD-Diff: Boundary-Frequency Feature-Enhanced Rail Surface D...

引用

10th International Conference on Systems and Informatics, ICSAI 2024

作者： Wang, Dezhou Su, Shixiang Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9798331510138

Rail surface defect inspection is an essential task for the railway system. However, due to the similarity of the background and defect foreground pixels, uneven textures, irregular shapes and multiple scales of the existing defects, the inspection accuracy is still required to be further improved. In this paper, we first expand our dataset by GAN-based method for the scarcity of the defect samples. Then, we propose a diffusion-based model to perform the classification and segmentation task. The diffusion model predicts the mask from the Gaussian noise broken ground truth by successive designed transformer decoder. Meanwhile, to better distinguish the pixels in the boundary or other illegible regions, a boundary-frequency feature enhancement module (BFM) is proposed to make the model pay more attention to the defect-related features. Experiments on the rail surface defect dataset revealed that the proposed diffusion-based transformer decoder and BFM can work well together and efficiently improve the rail surface defect segmentation accuracy. © 2024 IEEE.

关键词： Decoding

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Theoretical characterization of the temperature-dependent saturation magnetization of magnetic metallic materials

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Chinese Physics B 2024年第7期33卷 577-585页

作者：吴金龙董攀贺屹马艳丽李梓源姚沁远邱俊麻建坐李卫国 State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400044China College of Aerospace Engineering Chongqing UniversityChongqing 400044China College of Intelligent Systems Science and Engineering Hubei Minzu UniversityEnshi 445000China College of Mechanical Engineering and Automation Chongqing Industry Polytechnic CollegChongqing 401120China

Based on the force-heat equivalence energy density principle,a theoretical model for magnetic metallic materials is developed,which characterizes the temperature-dependent magnetic anisotropy energy by considering the equivalent relationship between magnetic anisotropy energy and heat energy;then the relationship between the magnetic anisotropy constant and saturation magnetization is ***,we formulate a temperature-dependent model for saturation magnetization,revealing the inherent relationship between temperature and saturation *** model predicts the saturation magnetization for nine different magnetic metallic materials at different temperatures,exhibiting satisfactory agreement with experimental ***,the experimental data used as reference points are at or near room *** to other phenomenological theoretical models,this model is considerably more accessible than the data required at 0 *** index included in our model is set to a constant value,which is equal to 10/3 for materials other than Fe,Co,and *** transition metals(Fe,Co,and Ni in this paper),the index is 6 in the range of 0 K to 0.65T_(cr)(T_(cr) is the critical temperature),and 3 in the range of 0.65T_(cr) to T_(cr),unlike other models where the adjustable parameters vary according to each *** addition,our model provides a new way to design and evaluate magnetic metallic materials with superior magnetic properties over a wide range of temperatures.

关键词： magnetic metallic materials temperature dependent saturation magnetization modeling

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