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Granular Computing-Based Fuzzy Deep Neural Network for Long-Tailed Fault Diagnosis: Design and Analysis

Expert systems with Applications 2025年

作者： Meng-Wei Li Zhen-Sheng Zang Wei Lu Witold Pedrycz School of Control Science and Engineering Dalian University of Technology Dalian Liaoning 116023 China LiaoHe Petroleum Engineering Co. Ltd PanJin 124010 China Department of Electrical and Computer Engineering University of Alberta Edmonton T6R 2V4 AB Canada Systems Research Institute Polish Academy of Sciences Warsaw 00-901 Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Istinye University Sariyer/Istanbul Turkiye

In real industrial settings, fault occurrences are typically infrequent, resulting in a significant imbalance between fault and normal samples – a phenomenon characterized as a long-tailed data distribution. Conventional deep learning approaches tend to overlook minority fault modes, thereby degrading fault diagnosis (FD) performance. To address this challenge, in this paper, a granule computing-based fuzzy deep neural network (GC-FDNN) model is proposed. The model incorporates a multi-view data augmentation unit that synthesizes additional fault samples through diverse strategies including noise injection and scale transformation, forming an augmented dataset that mitigates fault modes’ imbalance. Subsequently, the model employs a fuzzy feature information distillation unit to process this augmented dataset, extracting robust, compact, and representative fuzzy fault features through a novel architecture of sequentially stacked feature transformation blocks–each containing a fuzzy learning layer paired with a distillation layer–that systematically mitigates the uncertainty introduced through the data augmentation process while preserving discriminative fault characteristics. The final unit, an adaptive multi-faceted granular classifier with a Takagi-Sugeno-Kang structure, completes the mapping from the fault features to specific fault modes. This unit employs a multi-faceted granular performance loss metric to reshape fault features into fault mode-specific local neighborhood structures in hypersphere information granule (HSIG) form. The model can be optimized in end-to-end way. The main contribution of this work lies in the development of a two-stage feature refinement mechanism that integrates deep learning-based feature extraction with granular computing-based knowledge reasoning. In comparison with latest long-tailed FD methods, the proposed mechanism enhances the extraction of discriminative fault features in long-tailed scenarios by precisely characterizing cr

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Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

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Chinese Journal of Aeronautics 2019年第12期32卷 2679-2693页

作者： Yang XU Delin LUO Dongyu LI Yancheng YOU Haibin DUAN School of Aerospace Engineering Xiamen UniversityXiamen 361005China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Department of Electrical&Computer Engineering National University of SingaporeSingapore 117583Singapore

This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods,the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design,the controllers can be used to track different time-varying target formation patterns. Besides, multilayer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.

关键词： Affine formation control Collision avoidance Lyapunov stability Target enclosing Two-layer strategy

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Innovation, Research and Development in engineering Education. Activities of the Spanish Chapter of the IEEE Education Society: Directive Board of the IEEE Education Society Spanish Chapter 2020-2021

Innovation, Research and Development in Engineering Educatio...

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Technologies Applied to Electronics Teaching (TAEE)

作者： Ó scar Martí nez Bonastre Cristina Ferná ndez Lluí s Vicent Francisco Mur Manuel Castro Gabriel Diaz Jose Carpio Elio Sancristobal Sergio Martin Jose Sá nchez Francisco Javier Arcega Solsona Juan Suardiaz Muro Manuel Caeiro-Rodrí guez Martí n Llamas Inmaculada Plaza Baltasar Ferná ndez Manjó n Pedro Muñ oz-Merino Edmundo Tovar Telmo Zarraonandia Ayo Javier Garcia Zubia José Antonio Delgado Pení n Department of Statistics Mathematics and Computing Science Operations Research Centre Universidad Miguel Hern&#x00E1 ndez Elche Spain Department of Electronic Technology Universidad Carlos III de Madrid Madrid Spain UPF Barcelona School of Management Barcelona Spain Department of Electrical Electronic and Control Engineering UNED Madrid Spain Department of Electrical Engineering Universidad de Zaragoza Zaragoza Spain Department of Automatics Electrical Engineering and Electronic Technology Technical University of Cartagena Cartagena Spain atlanTTic Research Center University of Vigo Vigo Spain Department of Electronics and Communication Universidad de Zaragoza Zaragoza Spain Department of Software Engineering and Artificial Intelligence Complutense University of Madrid Madrid Spain Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Spain Department of Computer Languages and Systems and Software Engineering Universidad Polit&#x00E9 cnica de Madrid Madrid Spain Department of Computer Science and Engineering Universidad Carlos III de Madrid Madrid Spain Department of Electronic Engineering Universidad de Deusto Bilbao Spain Universitat Polit&#x00E8 cnica de Catalunya Barcelona Spain

ISBN: (数字)9781665421614

ISBN: (纸本)9781665421621

The Technical Committee of the CESEI (Spanish Chapter of the IEEE Education Society) is focused on the Innovation, Research and Development (I+R+D) of the education in engineering, mainly Electric and computer engineering. As in other interdisciplinary fields, the I+R+D involves several sources of information and different stakeholders, each one with its own focus and purpose. As a result, sometimes it may be complex for practitioners and researchers to identify the more appropriate entities for their interests. This paper shows how the CESEI Technical Committee tries to solve this difficulty by providing updated information regarding the main publications (journals), events (conferences) and awards to the best academic works. The paper focuses special attention on the activities held during 2020–2021.

关键词： Technological innovation Collaboration Stakeholders engineering education Research and development

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A framework for industrial symbiosis systems for agent-based simulation 21

A framework for industrial symbiosis systems for agent-based...

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21st IEEE Conference on Business Informatics, CBI 2019

作者： Fraccascia, Luca Yazdanpanah, Vahid Van Capelleveen, Guido Yazan, Devrim Murat Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Industrial Engineering and Business Information Systems University of Twente Enschede Netherlands

ISBN: (纸本)9781728106502

The industrial symbiosis (IS) practice refers to replacing production inputs with wastes generated by other production processes, thus helping to close the loop of manufacturing processes. Companies adopting IS can reduce the amounts of wastes disposed of in landfills and primary inputs used in production processes, enhancing their production efficiency and reducing their production cost. The Agent-based modeling (ABM) approach has been recently adopted to advance the knowledge in the IS field, in particular to explore the extent to which the establishment of IS relationships can be affected by policy measures, benefit-sharing contracts, information-sharing tools, or social factors. However, the agentbased models proposed in the literature are highly different in terms of agents considered, their attributes, possible actions, and decisional rules. In particular, these models might result far from the real world, in terms of how the agents are modeled, as well as on the actions that they can undertake. The aim of this paper is to provide a general framework on how to model IS systems with ABM in a comprehensive way. The paper provides a literature review on IS aimed at identifying the potential agents in IS, their attributes, and their potential actions, shaped by technical, economic, and regulatory issues affecting the behavior of agents in terms of strategic management. Based on the results of the literature review, a general framework is proposed and discussed. This paper is expected to advance the knowledge on ABM for IS by providing useful suggestions to modelers and academicians. © 2019 IEEE.

关键词： Autonomous agents

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A secure state estimation algorithm for nonlinear systems under sensor attacks

arXiv

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arXiv 2020年

作者： Chong, Michelle S. Sandberg, Henrik Hespanha, João P. Control Systems Technology section Department of Mechanical Engineering Eindhoven University of Technology Netherlands Division of Decision and Control Systems KTH Royal Institute of Techonology Sweden Electrical and Computer Engineering Department University of California Santa Barbara United States

The state estimation of continuous-time nonlinear systems in which a subset of sensor outputs can be maliciously controlled through injecting a potentially unbounded additive signal is considered in this paper. Analogous to our earlier work for continuous-time linear systems in [1], we term the convergence of the estimates to the true states in the presence of sensor attacks as ‘observability under M attacks’, where M refers to the number of sensors which the attacker has access to. Unlike the linear case, we only provide a sufficient condition such that a nonlinear system is observable under M attacks. The condition requires the existence of asymptotic observers which are robust with respect to the attack signals in an input-to-state stable sense. We show that an algorithm to choose a compatible state estimate from the state estimates generated by the bank of observers achieves asymptotic state reconstruction. We also provide a constructive method for a class of nonlinear systems to design state observers which have the desirable robustness property. The relevance of this study is illustrated on monitoring the safe operation of a power distribution network. Copyright © 2020, The Authors. All rights reserved.

关键词： State estimation

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On the Existence of Lagrange Multipliers in Distribution Network Reconfiguration Problems

arXiv

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arXiv 2025年

作者： Liu, Rong-Peng Song, Yue Wang, Xiaozhe Zeng, Bo Department of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada Department of Control Science and Engineering Tongji University Shanghai201804 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai201210 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai201210 China Department of Industrial Engineering Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15106 United States

Distribution network reconfiguration (DNR) is an effective approach for optimizing distribution network operation. However, the DNR problem is computationally challenging due to the mixed-integer non-convex nature. One feasible approach for addressing this challenge is to reformulate binary line on/off state variables as (continuous) non-convex constraints, leading to a nonconvex program. Unfortunately, it remains unclear whether this formulation satisfies the Karush-Kuhn-Tucker (KKT) conditions at locally optimal solutions. In this brief, we study the existence of Lagrange multipliers in DNR problems and prove that under mild assumptions, Lagrange multipliers exist for the DNR model at every locally optimal solution almost surely such that the KKT conditions hold. Copyright © 2025, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Virtual Staining of Label-Free Tissue in Imaging Mass Spectrometry

arXiv

引用

arXiv 2024年

作者： Zhang, Yijie Huang, Luzhe Pillar, Nir Li, Yuzhu Migas, Lukasz G. Van de Plas, Raf Spraggins, Jeffrey M. Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Mass Spectrometry Research Center Vanderbilt University NashvilleTN37232 United States Delft Center for Systems and Control Delft University of Technology Delft2628 Netherlands Department of Cell and Developmental Biology Vanderbilt University NashvilleTN37232 United States Department of Chemistry Vanderbilt University NashvilleTN37232 United States Department of Biochemistry Vanderbilt University NashvilleTN37232 United States Department of Pathology Microbiology and Immunology Vanderbilt University Medical Center NashvilleTN37232 United States Department of Surgery University of California Los AngelesCA90095 United States

Imaging mass spectrometry (IMS) is a powerful tool for untargeted, highly multiplexed molecular mapping of tissue in biomedical research. IMS offers a means of mapping the spatial distributions of molecular species in biological tissue with unparalleled chemical specificity and sensitivity. However, most IMS platforms are not able to achieve microscopy-level spatial resolution and lack cellular morphological contrast, necessitating subsequent histochemical staining, microscopic imaging and advanced image registration steps to enable molecular distributions to be linked to specific tissue features and cell types. Here, we present a virtual histological staining approach that enhances spatial resolution and digitally introduces cellular morphological contrast into mass spectrometry images of label-free human tissue using a diffusion model. Blind testing on human kidney tissue demonstrated that the virtually stained images of label-free samples closely match their histochemically stained counterparts (with Periodic Acid-Schiff staining), showing high concordance in identifying key renal pathology structures despite utilizing IMS data with 10-fold larger pixel size. Additionally, our approach employs an optimized noise sampling technique during the diffusion model’s inference process to reduce variance in the generated images, yielding reliable and repeatable virtual staining. We believe this virtual staining method will significantly expand the applicability of IMS in life sciences and open new avenues for mass spectrometry-based biomedical research. Copyright © 2024, The Authors. All rights reserved.

关键词： Tissue

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Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems

arXiv

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arXiv 2022年

作者： Wang, Yangyang Gill, Jeffrey P. Chiel, Hillel J. Thomas, Peter J. Department of Mathematics The University of Iowa Iowa CityIA52242 United States Department of Biology Case Western Reserve University ClevelandOH44106 United States Departments of Biology Neurosciencesand Biomedical Engineering Case Western Reserve University ClevelandOH44106 United States Departments of Mathematics Applied Mathematics and StatisticsBiologyCognitive ScienceData and Computer Scienceand Electrical Control and Systems Engineering Case Western Reserve University ClevelandOH44106 United States

Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al., 2015;Lyttle et al., 2017). We established in (Wang et al., 2021) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates’ hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing *** Codes 34C07, 34C15, 58E25, 49J52, 92B20, 93C73 Copyright © 2022, The Authors. All rights reserved.

关键词： Activation analysis

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Distributed Average Consensus under Quantized Communication via Event-Triggered Mass Splitting

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IFAC-PapersOnLine 2020年第2期53卷 2957-2962页

作者： Apostolos I. Rikos Christoforos N. Hadjicostis Division of Decision and Control Systems KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Department of Electrical and Computer Engineering at the University of Cyprus Nicosia Cyprus

We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the agents, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we present and analyze a distributed averaging algorithm which operates exclusively with quantized values (specifically, the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed distributed averaging protocol and show that its execution, on any time-invariant and strongly connected digraph, will allow all agents to reach, in finite time, a common consensus value that is equal to the quantized average. We conclude with comparisons against existing quantized average consensus algorithms that illustrate the performance and potential advantages of the proposed algorithm.

关键词： Quantized average consensus event-triggered distributed algorithms quantization digraphs multi-agent systems

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Combining Trajectory Data with Analytical Lyapunov Functions for Improved Region of Attraction Estimation

arXiv

引用

arXiv 2021年

作者： Lugnani, Lucas Jones, Morgan Alberto, Luís F.C. Peet, Matthew Dotta, Daniel Faculty of Electrical and Computer Engineering University of Campinas Brazil The Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom The São Carlos Engineering School University of São Paulo São Carlos Brazil The School for the Engineering of Matter Transport and Energy Arizona State University Tempe United States

The increasing uptake of inverter based resources (IBRs) has resulted in many new challenges for power system operators around the world. The high level of complexity of IBR generators makes accurate classical model-based stability analysis a difficult task. This paper proposes a novel methodology for solving the problem of estimating the Region of Attraction (ROA) of a nonlinear system by combining classical model based methods with modern data driven methods. Our method yields certifiable inner approximations of the ROA, typical to that of model based methods, but also harnesses trajectory data to yield an improved accurate ROA estimation. The method is carried out by using analytical Lyapunov functions, such as energy functions, in combination with data that is used to fit a converse Lyapunov function. Our methodology is independent of the function fitting method used. In this work, for implementation purposes, we use Bernstein polynomials to function fit. Several numerical examples of ROA estimation are provided, including the Single Machine Infinite Bus (SMIB) system, a three machine system and the Van-der-Pol system. Copyright © 2021, The Authors. All rights reserved.

关键词： Lyapunov functions

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