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Finite-control-Set Model Predictive control with Reduced Computational Burden in Cascaded H-Bridge Permanent Magnet Synchronous Motor Drives for EV Applications

Finite-Control-Set Model Predictive Control with Reduced Com...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Gemma, Filippo Riccio, Jacopo Tresca, Giulia Volpini, Andrea Zanchetta, Pericle University of Pavia Electrical Computer and Biomedical Engineering Dept Pavia Italy University of Nottingham Power Electronics Machines and Control Group Nottingham United Kingdom

ISBN: (纸本)9798350376067

This article introduces an enhanced Finite-control-Set Model Predictive control (FCS-MPC) for Permanent Magnet Synchronous Motor (PMSM) drives powered by Multi-level Cascaded H-Bridge (CHB) inverters. The work focuses on reducing the algorithm computational complexity for torque control operations, ensuring State of Charge (SOC) balancing and reduced switching losses. The innovation lies in the utilization of adaptive Look-up Tables (LUTs) and an ad hoc objective function. Simulation results are provided to confirm the effectiveness of the proposed control approach in achieving accurate drive control with reduced switching frequency and enhanced SOC management. Additionally, the computational overhead of the proposed approach was measured on the target control platform to validate the reduction in computing complexity. © 2024 IEEE.

关键词： Table lookup

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An Anomaly Localization Method for Large-Scale Micro-services 4

An Anomaly Localization Method for Large-Scale Micro-service...

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4th International Symposium on computer Technology and Information Science, ISCTIS 2024

作者： Zhao, Weiting Xu, Bintai Ma, Chao Zhu, Shaosong Tai, Yu Li, Gang State Grid Shandong Information & Telecommunication Company Jinan China North China Electric Power University School of Control & Computer Engineering Beijing China

ISBN: (纸本)9798350354560

As the scale of micro-service systems on the cloud continues to expand, the dependencies between micro-services become more and more complex. Service anomalies may continue to propagate with the call relationship, leading to a decrease in the overall availability of the system. In order to cope with large-scale micro-service systems with complex dependencies, this paper designs an anomaly location method MicroALLS suitable for large-scale micro-services. This method collects micro-service operation indicator data based on Istio;uses the anomaly detection module of the variational auto-encoder for anomaly detection;once an anomaly is detected, an improved random walk algorithm is used to accurately and efficiently locate the micro-service anomaly. We use the train-ticket micro-service system as a test environment to evaluate the positioning accuracy of this method. The experimental results show that the anomaly detection and accuracy of the method are improved compared with the comparison method. © 2024 IEEE.

关键词： Anomaly detection

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Integrating photovoltaic systems into HVAC control using fuzzy algorithms for optimizing thermal comfort 30

Integrating photovoltaic systems into HVAC control using fuz...

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30th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2024

作者： Boicu, Mihaela-Gabriela Dobrea, Marius-Alexandru Vasluianu, Mihaela Olteanu, Gabriela-Valentina Neculoiu, Giorgian University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Technical University of Civil Engineering of Bucharest Faculty of Hidrotechnics Bucharest Romania

ISBN: (纸本)9798331539511

This article presents a study on the use of photovoltaic panels for storing electrical energy intended to power an HVAC unit placed in a residential room. To highlight this aspect, two specific scenarios will be considered. Thus, we aim to analyze whether the generated and stored energy is sufficient to fulfil the thermal comfort requirements of the user, while also considering the primary objective of minimizing energy consumption. To achieve this goal, the HVAC unit will be controlled by implementing a fuzzy system that determines its optimal activation based on the comfort level obtained from the user. The fuzzy system presents as inputs both environmental parameters and specific personal perception parameters of the user. The research results provide an insight into the efficiency of implementing photovoltaic energy storage systems for residential applications and propose solutions for optimizing energy consumption in the context of ensuring adequate thermal comfort. Thus, the study contributes to the development of sustainable and personalized energy solutions for smart homes. © 2024 IEEE.

关键词： Thermal comfort

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Error Dependent Sampling to Reduce Transient Events in Event Based control 3

Error Dependent Sampling to Reduce Transient Events in Event...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Miguel-Escrig, Oscar Romero-Perez, Julio-Ariel Sanchez-Moreno, Jose Dormido-Bencomo, Sebastian Universitat Jaume I Department of System Engineering and Design Castelló de la Plana Spain Department of Computer Science and Automatic Control Madrid Spain

ISBN: (纸本)9798331540319

One of the objectives of event-based control is the reduction of generated events to perform an appropriate process control. Among the event generation techniques used to this end, those quantifying the error signal can be found more frequently for its simplicity of implementation. However, they entail a drawback in the form of trade-off between event generation and performance. Aiming to reduce the number of events, specifically in the transient response, without degrading the performance, an error dependent sampling scheme is studied in this work. © 2024 IEEE.

关键词： Electromagnetic transients

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Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

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computers, Materials & Continua 2023年第4期75卷 183-196页

作者： Samah Alshathri Ezz El-Din Hemdan Walid El-Shafai Amged Sayed Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Energy Engineering College of Engineering&TechnologyArab Academy for Science Technology&Maritime TransportSmart Village CampusEgypt

In recent years, Digital Twin (DT) has gained significant interestfrom academia and industry due to the advanced in information technology,communication systems, Artificial Intelligence (AI), Cloud Computing (CC),and Industrial Internet of Things (IIoT). The main concept of the DT isto provide a comprehensive tangible, and operational explanation of anyelement, asset, or system. However, it is an extremely dynamic taxonomydeveloping in complexity during the life cycle that produces a massive amountof engendered data and information. Likewise, with the development of AI,digital twins can be redefined and could be a crucial approach to aid theInternet of Things (IoT)-based DT applications for transferring the data andvalue onto the Internet with better decision-making. Therefore, this paperintroduces an efficient DT-based fault diagnosis model based on machinelearning (ML) tools. In this framework, the DT model of the machine isconstructed by creating the simulation model. In the proposed framework,the Genetic algorithm (GA) is used for the optimization task to improvethe classification accuracy. Furthermore, we evaluate the proposed faultdiagnosis framework using performance metrics such as precision, accuracy,F-measure, and recall. The proposed framework is comprehensively examinedusing the triplex pump fault diagnosis. The experimental results demonstratedthat the hybrid GA-ML method gives outstanding results compared to MLmethods like LogisticRegression (LR), Na飗e Bayes (NB), and SupportVectorMachine (SVM). The suggested framework achieves the highest accuracyof 95% for the employed hybrid GA-SVM. The proposed framework willeffectively help industrial operators make an appropriate decision concerningthe fault analysis for IIoT applications in the context of Industry 4.0.

关键词： Automated fault diagnosis control system ML AI CC IIoT digital twins genetic algorithm GA-ML technique

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A control Theoretic Study on Omnidirectional MAVs with Minimum Number of Actuators and No Internal Forces at Any Orientation 63

A Control Theoretic Study on Omnidirectional MAVs with Minim...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Ali, Ahmed Gabellieri, Chiara Franchi, Antonio Faculty Robotics and Mechatronics Department Enschede7500 AE Netherlands Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy

ISBN: (纸本)9798350316339

We propose a new multirotor aerial vehicle class of designs composed of a multi-body structure in which a main body is connected by passive joints to links equipped with propellers. We have investigated some instances of such class, some of which are shown to achieve omnidirectionality while having a minimum number of inputs equal to the main body Degrees of Freedom DoF's, only uni-directional positive thrust propellers, and no internal forces generated at steady state. After dynamics are derived following the Euler-Lagrange approach, an I/O dynamic feedback linearization strategy is then used to show the controllability of any desired pose with stable zero dynamics. We finally verify the developed controller with closed-loop simulations. © 2024 IEEE.

关键词： Feedback linearization

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Automatic Recognition of Whale and Dolphin Whistles Based on Visual Feature Extraction Approach 2

Automatic Recognition of Whale and Dolphin Whistles Based on...

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2nd IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2022

作者： Wu, Wei Feng, Huibin Junejo, Naveed Ur Rehman Qiu, Yuquan Yan, Jiaquan College of Computer and Control Engineering Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China University of Lahore Department of Computer Engineering Lahore Pakistan

ISBN: (纸本)9781665442763

Automatic recognition of marine mammals plays a significant role in the protection of endangered marine species, generally utilizing their vocalizations. In this paper, we propose a novel visual feature extraction approach for whale and dolphin signals incorporating variational mode decomposition (VMD) and Hilbert transform (VMD-HT) to construct the high-resolution time-frequency signatures and using gray level co-occurrence matrix (GLCM) to extort image features. Firstly, the objected signals are decomposed by VMD algorithm into multiple intrinsic mode functions (IMFs), which can capture local frequency features precisely. Secondly, the time-frequency signature of the objected signal with high resolution is constructed by linear superposition operation of each IMF time-frequency image depicted through Hilbert transform (HT). Thirdly, the image features are extracted using GLCM. Eventually, support vector machine (SVM) is adopted to validate the classification performance of the proposed method. The experimental results verify that the resolution improvement of time-frequency image attains the correct recognition rate and the proposed method accuracy is higher than the compared method about 11.11% © 2022 IEEE.

关键词： Variational mode decomposition

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A Hybrid Temporal-Magnitude Based Sampling for Event-Based control 3

A Hybrid Temporal-Magnitude Based Sampling for Event-Based C...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Miguel-Escrig, Oscar Sanchez-Moreno, Jose Romero-Perez, Julio-Ariel Dormido-Bencomo, Sebastian Universitat Jaume I Department of System Engineering and Design Castelló de la Plana Spain Department of Computer Science and Automatic Control Madrid Spain

ISBN: (纸本)9798331540319

In the current industrial environment, which is shifting towards an event-based control prone paradigm, sampling strategies in use must be revisited. Both temporal and magnitude dependent sampling strategies have been demonstrated to be suitable for control systems, reporting benefits in different categories. However, these sampling strategies also present some drawbacks, discussed in this contribution. Aiming to address some of these drawbacks, a new sampling strategy is proposed gathering characteristics of both predecessors. © 2024 IEEE.

关键词： Decentralized control

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Ante-Hoc Generation of Task-Agnostic Interpretation Maps

Ante-Hoc Generation of Task-Agnostic Interpretation Maps

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Akash Guna, R.T. Benitez, Raul Sikha, O.K. Amrita School of Engineering Department of Computer Science and Engineering Coimbatore India Universitat Politècnica de Catalunya BarcelonaTech Departament of Automatic Control Spain

ISBN: (纸本)9798350302493

Existing explainability approaches for convolutional neural networks (CNNs) are mainly applied after training (post-hoc) which is generally unreliable. Ante-hoc explainers trained simultaneously with the CNN are more reliable. However, current ante-hoc explanation methods mainly generate inexplicit concept-based explanations tailored to specific tasks. To address these limitations, we propose a task-agnostic ante-hoc framework that can generate interpretation maps to visually explain any CNN. Our framework simultaneously trains the CNN and a weighting network - an explanation generation module. The generated maps are self-explanatory, eliminating the need for manual identification of concepts. We demonstrate that our method can interpret classification, facial landmark detection, and image captioning tasks. We show that our framework is explicit, faithful, and stable through experiments. To the best of our knowledge, this is the first ante-hoc CNN explanation strategy that produces visual explanations generic to CNNs for different tasks. © 2023 IEEE.

关键词： computer vision

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Image Recognition of Concrete Electromagnetic Flaw Detection Based on Improved YOLOv7 24

Image Recognition of Concrete Electromagnetic Flaw Detection...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Yuan, Shuai Yuan, Ze He, Kai School of Computer Science and Engineering Shenyang Jianzhu University China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction China Shenyang Branch of National Special Computer Engineering Technology Research Center China School of Electrical and Control Engineering Shenyang Jianzhu University China

ISBN: (纸本)9798400716720

Owing to the invisibility characteristics of the interiors of concrete structures, nondestructive testing technologies are commonly employed to detect internal damage. Electromagnetic flaw detection technology, as a prominent nondestructive testing method, offers capabilities of strong penetration and precise imaging. However, the output images produced by this detection technology are usually reliant on subjective human judgment, and existing automatic detection algorithms have limitations in terms of accuracy. To enhance the accuracy of electromagnetic flaw detection images, this paper proposes improved YOLOv7 based detection method. First of all, the ACBlock convolution module is introduced to replace the original 3×3 convolution kernel for alleviating the loss of edge feature information caused by the sampling operation of the backbone network MP module. Next, in order to have more focus on the semantic features of small targets, a global attention mechanism (GAMAttention) is incorporated into the algorithm. Then, the FReLU activation function is adopted to enhance the algorithm sensitivity to image space. Finally, experiments are conducted on a self-created concrete flaw detection image dataset to illustrate the efficiency of the proposed algorithm. The results show that the mean Average Precision (mAP) value achieved by the improved algorithm is 95.85%. which has a significant improvement of 13.89% in comparison with the pre-improved YOLOv7 algorithm and surpasses other algorithms in the same domain. These findings represent that the proposed algorithm effectively enhances the accuracy of concrete electromagnetic flaw detection image detection. © 2024 ACM.

关键词： Nondestructive examination

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