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Synthesis of Decentralized Variable Gain Robust controllers with Guaranteed L2Gain Performance via Piecewise Lyapunov Functions for a Class of Uncertain Large-Scale Interconnected Systems 48

Synthesis of Decentralized Variable Gain Robust Controllers ...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Nagai, Shunya Oya, Hidetoshi Kubo, Tomohiro Matsuki, Tsuyoshi Niihama College Department of Electronics and Control Engineering Ehime Japan Tokyo City University Faculty of Knowledge Engineering Department of Computer Science Tokyo Japan Tokushima University Graduate School of Technology Industrial and Social Sciences Tokushima Japan

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

For a class of uncertain large-scale interconnected systems, a design method of decentralized variable gain robust controllers with guaranteed { mathcal{L}-{{2}}} gain performance based on piecewise Lyapunov functions is shown in this paper. Furthermore, LMI-based sufficient conditions for the existence of the proposed decentralized variable gain robust controller are shown. Finally, the effectiveness of the proposed robust controller is presented through a simple numerical example. © 2022 IEEE.

关键词： Lyapunov functions

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Evolution and Effectiveness of Loss Functions in Generative Adversarial Networks

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China Communications 2021年第10期18卷 45-76页

作者： Ali Syed Saqlain Fang Fang Tanvir Ahmad Liyun Wang Zain-ul Abidin School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Department of Computer Science Portland State UniversityPortland 97207U.S. School of Information and Communication Engineering South West Jiaotong UniversityChengdu 610031China

Recently,the evolution of Generative Adversarial Networks(GANs)has embarked on a journey of revolutionizing the field of artificial and computational *** improve the generating ability of GANs,various loss functions are introduced to measure the degree of similarity between the samples generated by the generator and the real data samples,and the effectiveness of the loss functions in improving the generating ability of *** this paper,we present a detailed survey for the loss functions used in GANs,and provide a critical analysis on the pros and cons of these loss ***,the basic theory of GANs along with the training mechanism are ***,the most commonly used loss functions in GANs are introduced and ***,the experimental analyses and comparison of these loss functions are presented in different GAN ***,several suggestions on choosing suitable loss functions for image synthesis tasks are given.

关键词： loss functions deep learning machine learning unsupervised learning generative adversarial networks(GANs) image synthesis

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MRI Brain Tumor Classification Using Optimized APSO-LLRBFNN 2

MRI Brain Tumor Classification Using Optimized APSO-LLRBFNN

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Krishna, Tiruveedula Gopi Sreenivas, Nune Ajay Kumar, M. Reddy, Chandra Sekhar Rathee, Davinder Sing Urgessa, Teklu College of Electrical Engineering and Computing Adama Science and Technology University Department of Computer Science and Engineering Adama Ethiopia Andhra Loyala institute of Engineering and Technology Department of Electrical and Electronics Engineering Vijayawada India College of Electrical Engineering and Computing Adama Science and Technology University Department of Electrical Power and Control Engineering Adama Ethiopia College of Electrical Engineering and Computing Adama Science and Technology University Department of ECE Adama Ethiopia

ISBN: (纸本)9798331505745

The research presents a new efficient machine learning method to classify brain tumors because this task remains vital in fighting the high incidence of brain cancers. The proposed approach unites all its operations including image segmentation with feature extraction and classification into a single processing system. This study uses Particle Swarm Optimization (PSO) and Adaptive PSO (APSO) methodologies to optimize Locally Linear Radial Basis Function Neural Network (LLRBFNN) resulting in PSO-LLRBFNN and APSO-LLRBFNN model implementations. The research examined the optimized APSO-LLRBFNN models against Support Vector Machines (SVM) and Least Mean Squares (LMS) based LLRBFNN classifier methods. Results from experiments show that APSO-LLRBFNN gives superior outcomes with 98.93% accuracy and takes 12.23 seconds for execution, which surpasses currently available methods. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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Towards an Integrated Framework for Fugitive Methane Source Localization and Monitoring in a Wireless Sensor Network

Towards an Integrated Framework for Fugitive Methane Source ...

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

作者： Amira Al Jawhari Yasmine Souissi Jawhar Ghommam Yassine Jamoussi Faisal Mnif Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Department of Engineering GUtech University Muscat Oman Laboratory of Control Energy Management (Cem-Lab) ENIS Tunisa Departement of Computer Science College of Science SQU

Gas leaks are the main cause of industrial fires and accidents. These cause countless fatalities, equipment damage, and other severe environmental effects. In this paper, we provide a framework for the monitoring and detection of methane leakage using a diffusion model based on the gas diffusion theory. Given that centralized Least Square methods are not efficient and robust as they require the gathering and processing of large-scale measurements on a central node. We propose a detection technique which makes use of the distributed (Non-linear) least squares method to overcome this problem. Then, a network of connected methane sensors is used to detect gas leaks. In order to estimate the parameters of the diffusive model for the gas leakage on each sensor node, a distributed recursive estimator of the consensus plus an innovation type technique is used. The characteristics being estimated include the gas source’s distance, which will be effectively triangulated to determine the source’s precise location. The targeted location is subsequently estimated using a location dispersed algorithm-based LS.

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State-Space Piece-Wise Affine System Identification with Online Deterministic Annealing

State-Space Piece-Wise Affine System Identification with Onl...

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European control Conference (ECC)

作者： Christos N. Mavridis Aris Kanellopoulos John S. Baras Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Department of Electrical and Computer Engineering and the Institute for Systems Research University of Maryland College Park USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We propose an online identification scheme for discrete-time piece-wise affine state-space models based on a system of adaptive algorithms running in two timescales. A stochastic approximation algorithm implements an online deterministic annealing scheme at a slow timescale, estimating the partition of the augmented state-input space that defines the switching signal. At the same time, an adaptive identification algorithm, running at a higher timescale, updates the parameters of the local models based on the estimate of the switching signal. Identifiability conditions for the switched system are discussed and convergence results are given based on the theory of two-timescale stochastic approximation. In contrast to standard identification algorithms for piece-wise affine systems, the proposed approach progressively estimates the number of modes needed and is appropriate for online system identification using sequential data acquisition. This progressive nature of the algorithm improves computational efficiency and provides real-time control over the performance-complexity trade-off, desired in practical applications. Experimental results validate the efficacy of the proposed methodology.

关键词： Switched systems Annealing Stochastic processes Switches Approximation algorithms Real-time systems System identification

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Nonlinear Study of SRG Configurations Using Finite Element Analysis

Nonlinear Study of SRG Configurations Using Finite Element A...

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International Middle-East Power System Conference, MEPCON

作者： Asmaa E. Abdo Walid A. M. Ghoneim Hamdy A. Ashour Electrical Engineering and Automatic Control Department Arab Academy for Science Technology and Maritime Transport Alexandria Egypt

ISBN: (纸本)9781665463645

This paper, presents the non-linear analysis of the most common configurations of Switched Reluctance Generators (SRG). Finite Element Analysis (FEA) of two-phase (4/2), three-phase (6/4), and four-phase (8/6) SRGs have been carried out using (ANSYS Maxwell 16 - 3D Modeler - Transient solution). The simulation process was performed utilizing the Asymmetric Half Bridge Converter (AHBC) model as an external excitation circuit for the SRG model. Research interests have been dedicated recently to SRG as a promising and reliable candidate in both low-speed and high-speed applications, especially for small-scale renewable applications. However, this study includes the non-linear validation for both the conventional short-pitched and the fully-pitched SRG winding configurations at low-speed simulation conditions. This study aims to analyze the non-linear performance of SRG and validate the influence of stator and rotor pole angles ( $\beta_{s}$ and $\beta_{r}$ ) variation in addition to the excitation current patterns on the induced output voltage. The dynamic performance of SRG has been simulated, with the exact description of rotor angular position, number of conductors per phase, and the excitation current pattern for each case study. The FE simulation was applied to the same SRG test model; i.e., the same dimensions, the same angular speed, and the same number of conductors per phase. Moreover, SRG FEA output results have been recorded and compared to the corresponding results delivered from a related SRG linear analysis study done by the authors; hence the final proposed design was highlighted for further prototype implementation. The outcome of this study provides the recommended SRG design that can generate the maximum induced output voltage for the same machine design parameters.

关键词： Solid modeling Renewable energy sources Analytical models Rotors Voltage Switches Conductors

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Robotic Anchoring System with Two Locomotion Modes for Preoperative Localization of Colorectal Cancer

Robotic Anchoring System with Two Locomotion Modes for Preop...

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IEEE International Conference on Robotics and Biomimetics

作者： Jiale Wang Hao Ren Liu Yang Haoxiang Zhao Ruijia Zhang Yajing Shen Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong Institute of Robotics and Automatic Information System Nankai University

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

At present, colorectal cancer is one of the most prevalent cancers in the world. Colectomy serves as an effective treatment option for this disease. Preoperative localization plays a vital role in the colectomy procedure. However, traditional preoperative localization techniques have a greater risk of infection and lower accuracy. Moreover, it is difficult for the previous anchoring robots to adapt to the unstructured environment of the GI tract because of their limited movement abilities. To address these challenges, this work develops a robotic anchoring system with two locomotion modes which can anchor in the designated position. Driven by the external magnetic field, the robot can achieve slipping and flipping in the stomach. When the gradients of the field increase, the robot is triggered to deploy the anchoring mechanism in the intestine. Two in vitro experiments are conducted in the stomach and intestine phantoms. The first experiment demonstrates that the robot system can achieve both slipping and flipping in the stomach and its average position error is 2.96mm. The second experiment shows that the robot system can anchor in the designated position near the tumor and can resist a peristalsis force of 0.82N from the intestine wall.

关键词： Location awareness Stomach Intestines Phantoms Colorectal cancer Resists Magnetic fields In vitro Robots Tumors

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Applying System Thinking to Learn from Accident of Modern automatic control Systems

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Chinese Journal of Electronics 2025年第2期23卷 409-414页

作者： Ru Niu Yuan Cao Xiaocheng Ge Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronics and Information Engineering National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Department of Computer Science University of York York UK

Modern societies increasingly rely on automatic control systems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events, rather than a simple cause-effect chain. We take railway Train control systems (TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP - one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.

关键词： Sociotechnical systems Analytical models Systematics Railway accidents Transportation Medical services Rail transportation Systems thinking Research and development Accidents

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Simple and Optimal Sublinear Algorithms for Mean Estimation

arXiv

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arXiv 2024年

作者： Bertolotti, Beatrice Russo, Matteo Schwiegelshohn, Chris Shyam, Sudarshan Department of Computer Science Aarhus University Åbogade 34 Aarhus N8200 Denmark Department of Computer Control Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

We study the sublinear multivariate mean estimation problem in d-dimensional Euclidean space. Specifically, we aim to find the mean µ of a ground point set A, which minimizes the sum of squared Euclidean distances of the points in A to µ. We first show that a multiplicative (1 + Ε) approximation to µ can be found with probability 1 − δ using O(Ε−1 log δ−1) many independent uniform random samples, and provide a matching lower bound. Furthermore, we give two sublinear time algorithms with optimal sample complexity for extracting a suitable approximate mean: 1. A gradient descent approach running in time O((Ε−1 + log log δ−1) · log δ−1 · d). It optimizes the geometric median objective while being significantly faster for our specific setting than all other known algorithms for this problem. 2. An order statistics and clustering approach running in time O ((Ε−1 + logγ δ−1) · log δ−1 · d) for any constant γ > 0. Throughout our analysis, we also generalize the familiar median-of-means estimator to the multivariate case, showing that the geometric median-of-means estimator achieves an optimal sample complexity for estimating µ, which may be of independent interest. © 2024, CC BY.

关键词： Consensus algorithm

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Resilient distributed optimization under mobile malicious attacks

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IFAC-PapersOnLine 2023年第2期56卷 997-1002页

作者： Yuan Wang Changxin Liu Hideaki Ishii Karl Henrik Johansson Department of Robotics Hunan University Changsha China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Computer Science Tokyo Institute of Technology Yokohama Japan

This article addresses the distributed optimization problem in the presence of malicious adversaries that can move within the network and induce faulty behaviors in the attacked nodes. We first investigate the vulnerabilities of a consensus-based secure distributed optimization protocol under mobile adversaries. Then, a modified resilient distributed optimization algorithm is proposed. We develop conditions on the network structure for both complete and non-complete directed graph cases, under which the proposed algorithm guarantees that the estimates by regular nodes converge to the convex combination of the minimizers of their local functions. Simulations are carried out to verify the effectiveness of our approach.

关键词： Fault-tolerant distributed optimization multi-agent systems network security mobile adversary agents

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