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Consideration on RT software implementation for algorithm switching in MM structures

Consideration on RT software implementation for algorithm sw...

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International Conference on system Theory, control, and Computing (ICSTCC)

作者： Ciprian Lupu Catinca Secuianu Luu Duch Lich Faculty of Automatic Control and Computers University Politehnica Bucharest Bucharest Romania Faculty of Chemical Engineering and Biotechnologies University Politehnica Bucharest Bucharest Romania Faculty of Transportation Mechanical Engineering University of Science and Technology The University of Danang Da Nang Vietnam

Real-time (RT) implementation of control systems for non-linear processes raises numerous theoretical and practical challenges. Multi-model structures (MM) represent one of the successful solutions for these processes. However, switching of control algorithms constitutes the specific problem of MM structures. Even if reducing the sampling period can increase the precision in the control of some processes, for the case of algorithms switching in the MM structures is not improving significantly. The tests carried out in this work confirm this behavior for some numeric PIDs algorithms. Moreover, these tests can be an example for reducing the computational effort by changing the sampling period up to a maximum limit, specific to the ***, superior performances in switching control algorithms can be obtained by using a common database for all switched algorithms in the respective MM structure. The architecture proposed in the paper and the tests performed on a laboratory implementation prove these solutions.

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An Efficient and Secured Energy Management system for Automated Guided Vehicles

An Efficient and Secured Energy Management System for Automa...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Mrozek, Dariusz National Taiwan University Department of Computer Science and Information Engineering Taiwan Western Norway University of Applied Sciences Department of Computer Science Electrical Engineering and Mathematical Sciences Norway Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Poland

ISBN: (纸本)9781665480451

In this paper, we propose a Secure Energy Management system (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning network to simultaneously classify suppliers and predict the real supply quantities. The Q-learning decision module can then determine operating reserve and subsidies to manage the energy grid. Experimental results illustrate that the proposed anomaly detection module has an excellent performance in classifying malicious suppliers, excels at shaping supply distribution, and outperforms the existing benchmark systems. © 2022 IEEE.

关键词： Energy management

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Learning-based NLOS Detection and Uncertainty Prediction of GNSS Observations with Transformer-Enhanced LSTM Network

Learning-based NLOS Detection and Uncertainty Prediction of ...

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International Conference on Intelligent Transportation

作者： Haoming Zhang Zhanxin Wang Heike Vallery Institute of Automatic Control Faculty of Mechanical Engineering RWTH Aachen University Aachen Germany Department of BioMechanical Engineering Department for Rehabilitation Medicine Delft University of Technology Rotterdam The Netherlands

The global navigation satellite systems (GNSS) play a vital role in transport systems for accurate and consistent vehicle localization. However, GNSS observations can be distorted due to multipath effects and non-line-of-sight (NLOS) receptions in challenging environments such as urban canyons. In such cases, traditional methods to classify and exclude faulty GNSS observations may fail, leading to unreliable state estimation and unsafe system operations. This work proposes a deep-learning-based method to detect NLOS receptions and predict GNSS pseudorange errors by analyzing GNSS observations as a spatio-temporal modeling problem. Compared to previous works, we construct a transformer-like attention mechanism to enhance the long short-term memory (LSTM) networks, improving model performance and generalization. For the training and evaluation of the proposed network, we used labeled datasets from the cities of Hong Kong and Aachen. We also introduce a dataset generation process to label the GNSS observations using lidar maps. In experimental studies, we compare the proposed network with a deep-learning-based model and classical machine-learning models. Furthermore, we conduct ablation studies of our network components and integrate the NLOS detection with data out-of-distribution in a state estimator. As a result, our network presents improved precision and recall ratios compared to other models. Additionally, we show that the proposed method avoids trajectory divergence in real-world vehicle localization by classifying and excluding NLOS observations.

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Optimizing Grid-Connected Microgrid Energy Management Through Advanced Heuristic Algorithms 3

Optimizing Grid-Connected Microgrid Energy Management Throug...

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3rd International Conference on Advanced Electrical engineering, ICAEE 2024

作者： Adamou, A. Amadou Djehaf, M.A. Kobibi, Y.I. Djilani Rezkallah, M. Feddaoui, A. Pauwes Pan African University Institute of Water and Energy Sciences incl. Climate Change Tlemcen University Tlemcen3000 Algeria Djillali Liabes University Faculty of Electrical Engineering Department of Automatic Control Sidi Bel-Abbes22000 Algeria Mustapha Stambouli University Faculty of Sciences and Technology Department of Electrical Engineering Mascara29000 Algeria Sept-IlesQC Canada Badji Mokhtar University Department of Electromechanical dept Genie Electromécanique Laboratory Annaba23000 Algeria

ISBN: (纸本)9798350349351

In response to the urgent need for renewable energy development and variability management due to escalating population growth, rising energy demands, and diminishing natural reserves, this research focuses on optimizing energy management within a grid-connected microgrid. The study uniquely employs advanced heuristic algorithms to define system choices and constraints, achieving significant improvements in energy efficiency and cost reduction. Utilizing Matlab Simulink and Stateflow environments, various simulation scenarios are explored to demonstrate the benefits of the proposed approach, including enhanced stability and reliability of the energy supply. The findings highlight the potential for significant advancements in microgrid energy management through innovative algorithmic strategies. © 2024 IEEE.

关键词： connected mode EMS Energy management system Algorithm Heuristic Microgrid

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Vehicle type recognition based on audio data 58

Vehicle type recognition based on audio data

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58th Hawaii International Conference on system Sciences, HICSS 2025

作者： Kobiela, Dariusz Hajdasz, Michal Erezman, Mateusz Nurzyńska, Karolina Zaporowski, Szymon Kurowski, Adam Weichbroth, Pawel Department of Software Engineering Faculty of Electronics Telecommunication and Informatics Gdańsk University of Technology Gabriela Narutowicza 11/12 Gdańsk80-233 Poland Department of Multimedia Systems Faculty of Electronics Telecommunication and Informatics Gdańsk University of Technology Gabriela Narutowicza 11/12 Gdańsk80-233 Poland Department of Algorithmics and Software Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9780998133188

Identifying different vehicle types can help manage traffic more efficiently, reduce congestion, and improve public safety. This study aims to create a classification model that can recognize vehicle types based on the sound of passing vehicles. To achieve this, a database of raw audio files containing 1763 samples from two sources was assembled. The time-domain signals were converted to a time-frequency representation using the short-time Fourier transform to generate Mel Spectrograms. Mel-frequency Cepstral Coefficients (MFCCs) were also generated using the discrete cosine transform. In our experiments we compared these approaches. Since the data was imbalanced we applied online augmentation. Based on the literature review, we chose a Convolutional Neural Network (CNN) classifier because it is particularly well suited for analyzing large datasets due to its automatic feature extraction, parameter sharing and sparsity. The results showed that Mel Spectrograms were more effective for audio data preprocessing in this particular use case, achieving the highest accuracy of 0.875 and the highest f1-score of 0.877 compared to MFCCs. © 2025 IEEE Computer Society. All rights reserved.

关键词： Image coding

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Design of LQR controller for 3D Trajectory Tracking of Octocopter Unmanned Aerial Vehicle

Design of LQR Controller for 3D Trajectory Tracking of Octoc...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Jasmin Velagić Nedim Osmić Vedin Klovo Halil Lač ević Department od Automatic Control and Electronics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9781665496070

ISBN: (纸本)9781665496087

The paper deals with the mathematical modeling and control of an unmanned aerial vehicle (UAV), called octocopter, based on a linear quadratic regulator (LQR). The complex multivariable and nonlinear UAV model is linearized and represented in the state space form. Optimal LQR control system, which is composed of combination the altitude (UAV height - ${z}$ position) and attitude (orientation) controllers, was first designed. Then, this system is extended to provide an additional control of the translation movement in ${x}$ and ${y}$ directions. The proposed LQR control structure is capable of controlling the UAV for all position and orientation coordinates while tracking desired 3D trajectory. Simulation studies are performed on the UAV model where the designed LQR controller has been compared with previously developed PD controller.

关键词： Weight measurement Three-dimensional displays Attitude control Trajectory tracking Autonomous aerial vehicles Mathematical models Trajectory

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Design of Observer-Based Adaptive Fuzzy Fault-Tolerant control for Pneumatic Active Suspension with Displacement Constraint

Design of Observer-Based Adaptive Fuzzy Fault-Tolerant Contr...

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2023 International Conference on system Science and engineering, ICSSE 2023

作者： Ho, Cong Minh Dao, Hoang Vu Tran, Duc Thien Ahn, Kyoung Kwan Ho Chi Minh City University of Technology and Education Faculty of Mechanical Engineering Ho Chi Minh City70000 Viet Nam University of Ulsan School of Mechanical and Automotive Engineering Ulsan Korea Republic of Ho Chi Minh City University of Technology and Education Department of Automatic Control Ho Chi Minh City70000 Viet Nam

ISBN: (纸本)9798350322941

This study deals with the fault tolerance problem of an active air suspension system considering parametric uncertainties and sprung mass displacement in the event of sensor fault and unmeasured signals. A pneumatic spring is used to set up a quarter of the car model to investigate the flexible stiffness and provide an active force that can suppress chassis vibrations. To approximate unknown nonlinear parameters of air spring actuator dynamics, fuzzy logic systems (FLSs) are used as function approximators. Sensor failure is considered while all system states are assumed to be unmeasured variables. A fuzzy state observer is then designed to approximate the unknown system states and overcome the effective loss of sensor fault. Adaptive fault-tolerant control based on command filter backstepping technique to solve the problem of exploding complexity. To enhance tracking accuracy, this study involves a prescribed performance technique such that the sprung mass displacement is guaranteed between the predefined boundaries. Finally, the effectiveness of the proposed control is verified by comparative simulation examples under the presence of sensor fault and unknown system states. © 2023 IEEE.

关键词： Active suspension systems

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Intelligent control for Pressurizer system in Nuclear Power Plants 6

Intelligent Control for Pressurizer System in Nuclear Power ...

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6th International conference on Advanced Technology and Applied Sciences, ICaTAS 2021

作者： Sheta, A.A. Ali, E.H. Fikry, R.M. Mahmoud, T.A. El-Araby, S.M. Mahmoud, M.I. Engineering Department Nuclear Research Centre Egyptian Atomic Energy Authority Egypt Automatic Control and Industrial Electronics Department Faculty of Electronic Engineering Menoufya University Egypt

Fine control of output power for nuclear power plants is the essential goal for safe operation. In this work, a Fuzzy analytical proportional-integral-derivative (FPID) controller with different configurations is designed to adjust and control the pressure of the PZR system. The stability analysis of the FPID controller with variable gains is established, and conditions for bounded-input bounded-output stability conditions (BIBO) are derived using the small gain theory. Two scenarios are applied for evaluating the dynamic response of applied controllers. In addition, performance indices are compared between the PZR model and data measured from the PCtran VVER-1200 simulator. Finally, a simulation platform is developed for MATLAB / Simulink to implement the three-region nonlinear non-equilibrium PZR model and the designed pressure controllers. The analysis and evaluation results showed good durability of the designed controllers and satisfactory performance of the control. These results further show that the nonlinear PZR model is accurate, feasible, and valuable for dynamic simulation and control unit design. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Nuclear power plants

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A Review of Manufacturing Technologies of Soft Magnetic Composites for Electric Machines

A Review of Manufacturing Technologies of Soft Magnetic Comp...

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International Conference on Modern Electrical and Energy systems (MEES)

作者： Roman Manko Rieznik Dmytro Mario Vukotić Urban Rupnik Damijan Miljavec Selma Čorović Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

In this article the review of the existing manufacturing technologies of the soft magnetic materials have been performed. The existing technological protocols for production of the electrically insulated powders and their further treatment towards manufacturing of the soft magnetic materials are provided. The influences of different technological processes on the mechanical, electrical and magnetic properties of the resulting soft magnetic materials have been reviewed and described. Finally, the usage and implementation of the soft magnetic composites in the field of electric motor design have been discussed.

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Using the LQI2R control Method on the Adaptive Cruise control system for a Platoon of Vehicles 7

Using the LQI2R Control Method on the Adaptive Cruise Contro...

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7th International Scientific Conference on Applying New Technology in Green Buildings, ATiGB 2022

作者： Luu, Duc Lich Pham, Huu Truyen Pham, Quoc Thai Lupu, Ciprian Van Nguyen, Thien Vinh University of Technology Education Nghe An Vinh City Viet Nam Fac. of Transp. Mechanical Engineering the University of Danang-University of Science and Technology Danang Viet Nam Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Academy of Science and Technology Hanoi Viet Nam

ISBN: (数字)9781665472852

ISBN: (纸本)9781665472852

Autonomous vehicles refer to vehicles whose operations and actuations are directed towards fully controlled. However, we need a long transition period where drivers of vehicles with different levels of partial automation will be responsible for the driving function. The Adaptive Cruise control (ACC) is one of the key subsystems of Advanced Driver Assistance systems that have attracted considerable research and development efforts due to their multifaceted advantages such as increasing the urban arterial capacity, improve traffic safety with shorter inter-vehicle spacing between vehicles [1], [2]. This study proposes a Linear Quadratic Integral Regulator with double integrator (LQI2R) for ACC technology in a platoon by using radars. An important criterion in ACC controller design is string stability which is analyzed by using a frequency-domain approach and Nyquist diagram within considering the different values of the constant headway time. The main purpose of platoon control is to keep the desired inter-vehicle distance while guaranteeing string stability requirements. The numerical simulations are carried out to validate the effectiveness of our results. © 2022 IEEE.

关键词： Adaptive cruise control

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