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18th International Conference on Intelligent Systems and Knowledge engineering, ISKE 2023

作者： Zhong, Jian Liu, Peiyao Chen, Shuwei School of Computer and Software Engineering National-Local Joint Engineering Laboratory of System Credibility Automatic Verification Xihua University Chengdu China

ISBN: (纸本)9798350318401

Machine learning has been a prominent research focus in recent years, and integrating machine learning methods into automated theorem provers has become a current trend in theorem proving research. Standard contradiction separation rule is a newly proposed multi-clause, dynamic, and synergized deductive inference rule. The key aspect of standard contradiction separation rule is how to plan deduction paths. In order to better plan the deduction path, this paper explores the dynamic learning within the process of contradiction separation deduction and introduces a novel active deductive heuristic algorithm based on reinforcement learning. Experimental results demonstrate that this new algorithm enhances the reasoning capability of the theorem prover Prover9. © 2023 IEEE.

关键词： Reinforcement learning

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Constrained multi-cluster game: Distributed Nash equilibrium seeking over directed graphs 63

Constrained multi-cluster game: Distributed Nash equilibrium...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Nguyen, Duong Thuy Anh Bianchi, Mattia Dorfler, Florian Nguyen, Duong Tung Nedic, Angelia Arizona State University Tempe School of Electrical Computer and Energy Engineering AZ United States Automatic Control Laboratory Eth Zürich Switzerland

ISBN: (纸本)9798350316339

Motivated by the complex dynamics of cooperative and competitive interactions within networked agent systems, multi-cluster games provide a framework for modeling the interconnected goals of self-interested clusters of agents. For this setup, the existing literature does not provide comprehensive gradient-based solutions that simultaneously address constraint sets and directed communication networks-both of which are essential for many practical applications-due to the complexities posed by the projection and the imbalanced mixing matrix. To address this gap, this paper proposes a distributed Nash equilibrium seeking algorithm that integrates consensus-based methods and gradient-tracking techniques, utilizing row-stochastic weight matrices for inter-cluster communication and column-stochastic weight matrices for intracluster communication. To handle constraints, we introduce an averaging procedure to control errors introduced by projection methods within the gradient-tracking procedure. We establish the linear convergence of the proposed algorithm, focusing on the contraction property of the optimality gap. The efficacy of the algorithm is demonstrated through its application to microgrid energy management. © 2024 IEEE.

关键词： Stochastic systems

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Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning 35

Microservice Deployment for Satellite Edge AI Inference via ...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yu, Zhiyong Cheng, Hei Victor Yang, Zhanpeng Liu, Xin Jiang, Yuning Zhou, Yong Shi, Yuanming ShanghaiTech University School of Information Science and Technology Shanghai201210 China Aarhus University Department of Electrical and Computer Engineering Denmark Automatic Control Laboratory Switzerland

ISBN: (纸本)9798350362244

Artificial intelligence (AI) is critical in evolving 5G and developing 6G networks, running on edge devices, and solving resource management challenges. The burgeoning number of edge devices draws attention to the potential of low-earth orbit (LEO) satellite networks with their onboard computing capabilities for edge inference. This paper explores LEO scenarios where multiple remote sensing edge AI inference tasks concurrently process data from a single source. However, due to there being parts with the same functions between different AI applications, traditional monolithic edge AI architecture must be deployed repeatedly and falls short in efficiently harnessing the heterogeneous resources of LEO satellite networks. To solve this problem, we utilize the microservice architecture to decouple a single AI application into several independent microservices to reuse these same functions. However, due to the high latency caused by multiple microservices' communication, we need to design a deployment strategy to fully utilize resources to reduce the service latency. We present a microservice deployment model to minimize the total service latency across all AI applications and meet resource constraints with the constraints of hardware, energy, and memory limitations. This latency optimization problem is rewritten as a Markov decision process (MDP) to effectively deal with the challenge posed by the time-varying transmission rate caused by satellite mobility. To increase the training data utilization, we employ a Proximal Policy Optimization (PPO) based reinforcement learning algorithm to meet the dynamic environment challenge. Finally, we obtain a sub-optimal solution with minimal accuracy loss and an acceptable solution time. © 2024 IEEE.

关键词： Markov processes

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Comparative analysis of the MPPT methods employed in the PV system, involving incremental conductance control and sliding mode control 2

Comparative analysis of the MPPT methods employed in the PV ...

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2nd International Conference on Energy Transition and Security, ICETS 2023

作者： Tahiri, Fadila Harrouz, Abdelkader Bostanci, Gazi Erkan Hartani, Mohamed Amine Badoud, Abdessalam Zemitte, Seddik Yaichi, Ibrahim Maatallah, Elabbes Adrar Algeria Ankara University Computer Engineering Department Turkey University of Ferhat Abbas Setif 1 Automatic Laboratory Setif Algeria

ISBN: (纸本)9798350372182

The objective of this research paper is to investigate diverse strategies for achieving optimal maximum power point tracking (MPPT) in photovoltaic (PV) systems. The research delves into the evaluation and comparison of two distinct MPPT techniques: incremental conductance (InC) and sliding mode control (SMC). A DC/DC boost converter is employed between the PV system and the load to facilitate the efficient transfer of the maximum available power. Conventional MPPT methods, such as InC, have shown limitations in detecting and accurately tracking the high point, resulting in a notable power loss. To address this issue, a proposed solution is the utilization of sliding mode control. This method has a number of benefits, including as accurate reference tracking, low distortion in current output, and resilience to changes in parameters. However, a challenge with this technique is the occurrence of pronounced oscillations during transitional periods. The results of simulation confirm that the outcomes achieved through The MPPT SMC outperforms the MPPT INC in relation to tracking the MPP, leading to reduced power losses. This suggests an improvement in the overall efficiency of the system. Additionally, the voltage and current are higher than in MPPT with InC. However, oscillations are more noticeable when using MPPT with SMC. © 2023 IEEE.

关键词： Sliding mode control

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Contribution to Asymmetrical Compensation through Parallel Controllers of FACTS (STATCOM)—IPC 240 Dual for a Power Transmission Line

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World Journal of engineering and Technology 2023年第1期11卷 20-40页

作者： Kengne Chatue Charlène Steva Mengata Mengounou Ghislain Koko Koko Joseph Batassou Guilzia Jeannot Nneme Nneme Leandre Laboratory of Computer and Automatic Engineering UFD of Engineering Sciences ENSET University of Douala Douala Cameroon

This work is part of the resolution of problems encountered on a 225 KV MANGOMBE-OYOMABANG line. This line is characterized by important technical losses, so that the voltage injected in the busbar is always lower than 200kV. The main objective of this work is to show the new solutions that can provide a combined FACTS-STATCOM and IPC 240 dual system on this line. Then to show the limitation of STATCOM compared to RPI 240. The results obtained allowed us to observe that in symmetrical operation the STATCOM improves the voltage profile on the busbar and in asymmetrical operation we found that it continues to regulate the voltage of each phase despite the unbalance. But the system remains too unbalanced because of the sequence current flow. The IPC 240 corrects this limitation, allowing asymmetrical operation of the line in an emergency while providing continuous service to the load.

关键词： FACTS STATCOM IPC 240 Dual Symmetry Asymmetry Contingency Voltage Profile

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Sensor Fault Detection and Identification of a Photovoltaic System Based on Sliding Mode Observer

Sensor Fault Detection and Identification of a Photovoltaic ...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Maouadda Ismail Karim Dahech Laboratory of “sciences and techniques of automatic control & computer engineering ” University of Sfax Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

The growing emphasis on sustainability and green energy in electricity generation has led researchers to focus on improving photovoltaic systems. Consequently, a reliable fault diagnosis method is crucial for protecting and maintaining the performance of PV systems. This paper introduces a fault detection approach utilizing a sliding mode observer to detect sensor faults in a standalone photovoltaic system. The method is based on residual generation, which identifies faults by comparing residuals with specific threshold values. The standalone photovoltaic test bench includes a boost converter that facilitates maximum power point tracking using the perturb and observe method for the load. Simulations are carried out in MATLAB/Simulink under stable temperature and varying irradiance conditions to evaluate the effectiveness and robustness of the proposed fault detection technique.

关键词： Photovoltaic systems Fault diagnosis Temperature sensors Maximum power point trackers Uncertainty Fault detection System performance Observers Robustness Sustainable development

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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm

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Energy Reports 2023年 10卷 3113-3124页

作者： Attouri, Khadija Dhibi, Khaled Mansouri, Majdi Hajji, Mansour Bouzrara, Kais Nounou, Mohamed Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine1200 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Qatar Chemical Engineering Program Texas A&M University at Qatar Qatar Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir 5019 Tunisia

This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. The approach unfolds in three integral phases. Firstly, the establishment of interval centers and ranges, employing upper and lower bounds, effectively manages the inherent uncertainties arising from noise and measurement errors intrinsic to the wind system. Subsequently, the dataset undergoes processing via the Sine-Cosine Optimization Algorithm (SCOA), enabling the extraction of the most pertinent attributes. The culmination of predictive precision and classification performance is achieved through the integration of the refined dataset into an ensemble learning paradigm, harmonizing bagging, boosting techniques, and an artificial neural network classifier. The principal aim of the IEL-SCOA approach is to discern the spectrum of operational conditions within WEC systems, encompassing a healthy mode alongside six distinct faulty modes. These anomalies, encompassing short circuits, open circuits, and wear-out incidents, are deliberately induced at diverse locations and facets of the system, notably the generator and grid sides. Empirical results underscore the robustness and efficiency of the proposed methodology, showcasing an exceptional accuracy rate of 99.76 %. These outcomes definitively establish the IEL-SCOA approach as a potent and efficacious tool for precise fault diagnosis in uncertain WEC systems. © 2023

关键词： Fault detection

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Supervised machine learning-based salp swarm algorithm for fault diagnosis of photovoltaic systems

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Journal of engineering and Applied Science 2024年第1期71卷 12页

作者： Hichri, Amal Hajji, Mansour Mansouri, Majdi Nounou, Hazem Bouzrara, Kais Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kairouan Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Monastir5019 Tunisia

The diagnosis of faults in grid-connected photovoltaic (GCPV) systems is a challenging task due to their complex nature and the high similarity between faults. To address this issue, we propose a wrapper approach called the salp swarm algorithm (SSA) for feature selection. The main objective of SSA is to extract only the most important features from the raw data and eliminate unnecessary ones to improve the classification accuracy of supervised machine learning (SML) classifiers. Subsequently, the selected features are used to train supervised machine learning (SML) techniques in distinguishing between various operating modes. To evaluate the efficiency of the technique, we used healthy and faulty data from GCPV systems that have been injected with frequent faults, 20 different types of faults were introduced, including line-to-line, line-to-ground, connectivity faults, and those affecting the operation of bay-pass diodes. These faults present diverse conditions, such as simple and multiple faults in the PV arrays and mixed faults in both arrays. The performances of the developed SSA-SML are compared with those using principal component analysis (PCA) and kernel PCA (KPCA) based SML techniques through different criteria (i.e., accuracy, recall, precision, F1 score, and computation time). The experimental findings demonstrated that the proposed diagnosis paradigm outperformed the other techniques and achieved a high diagnostic accuracy (an average accuracy greater than 99%) while significantly reducing computation time. © 2023, The Author(s).

关键词： Failure analysis

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Energy-balancing dual-port grid-forming control for VSC-HVDC systems

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IFAC-PapersOnLine 2023年第2期56卷 6447-6452页

作者： Irina Subotić Dominic Groß Automatic Control Laboratory ETH Zürich Switzerland Department of Electrical and Computer Engineering University of Wisconsin-Madison USA

This work examines energy-balancing dual port grid-forming (GFM) control for high-voltage direct current (HVDC) transmission. In contrast to the state-of-the-art, HVDC converters controlled in this way do not require assigning GFM and grid-following roles to different converters. Moreover, this control enables primary frequency control and inertia support through HVDC links. A detailed stability and steady-state analysis results in conditions on the control gains such that i) the overall hybrid dc/ac system is stable, ii) asynchronous ac areas are quasi-synchronous, and iii) circulating power in cyclic topologies is avoided. Finally, a high-fidelity case study is used to illustrate and verify the analytical results.

关键词： Power systems Power systems stability Grid-forming control HVDC transmission

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On the Stabilization of a Class of OSL Conformable Fractional Order Nonlinear Systems 11

On the Stabilization of a Class of OSL Conformable Fractiona...

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11th IEEE International Conference on Systems and Control, ICSC 2023

作者： Alsharif, Ali Omar M. Jmal, A. Naifar, O. Ahmed, Ausama H. Gassara, Hamdi Makhlouf, A. Ben Electrical Engineering Department BP 1173 Sfax3038 Tunisia Elmergib University Faculty of Engineering Department of Electrical & Computer Engineering Alkhums Libya National School of Engineering of Sfax University of Sfax Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering Tunisia Faculty of Sciences of Sfax Department of Mathematics Route Soukra BP 1171 Sfax3000 Tunisia

ISBN: (纸本)9798350304886

One-Sided Lipschitz (OSL) fractional order modeling is a top choice for solving the stabilization issue of nonlinear systems. Despite numerous studies on the subject, there remains a gap in understanding when it comes to fractional calculus. By providing a stabilizing strategy for a certain type of OSL fractional order nonlinear systems, this study fills the gap. A numerical example demonstrating the correctness of the suggested approach and demonstrating its efficacy for the tested class. © 2023 IEEE.

关键词： Stabilization

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