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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Allan Christian Krainski Ferrari Gideon Villar Leandro Leandro dos Santos Coelho Eletrical Engineering Department Federal University of Paraná UFPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) Federal University of Paraná (UFPR) and Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR)

This article implements the multi-objective grey wolf optimizer (MOGWO) in the identification process of a multivariable system. For a sequence of 100 runs, MOGWO approach had compared and analyzed with the grey wolf optimizer (GWO), the single-objective version. In the computational simulation, the determination coefficient values and mean square error had used to analyze the quality of the models obtained. In the results, MOGWO showed superior to GWO to the differences between the order of magnitude of the system outputs. The implementation shows that MOGWO and other multi-objective metaheuristics can be an alternative method to solve problems of identification processes of multivariable systems.

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A Systematic Literature Mapping of Path Planning and Collision Avoidance Approaches for Unmanned Fixed-Wings

A Systematic Literature Mapping of Path Planning and Collisi...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Elias J. R. Freitas Miri W. Cohen Frederico G. Guimarães Luciano C. A. Pimenta Graduate Program in Electrical Engineering Federal Institute of Minas Gerais IFMG and Universidade Federal de Minas Gerais UFMG Belo Horizonte MG Brazil Braude College of Engineering Karmiel Israel Universidade Federal de Minas Gerais UFMG Brazil

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

In the rapidly evolving world of Unmanned Aerial Vehicles (UAVs), fixed-wing aircraft stand out for their remarkable efficiency and long-range endurance. The path planning and collision avoidance approaches for these UAVs must also take into account other constraints, such as the maximum curvature and pitch/climb angle, which are different from quadrotor drones. This paper presents a systematic literature mapping (SLM) in this context, which provides an overview of path planning and collision avoidance approaches developed for fixed-wing unmanned aerial vehicles in the last decade. Using Scopus and Web of Science databases, we extracted and analyzed data using the PICOC framework (Population, Intervention, Comparison, Outcome, and Context). Based on our inclusion and exclusion criteria, we identified 345 relevant articles for review. We applied an unsupervised classifier to cluster these approaches into domains systematically. This aims to highlight key topics, publication venues, and insights into the challenges and opportunities associated with path planning and collision avoidance for autonomous fixed-wing aircraft.

关键词： Systematics Trajectory tracking Atmospheric modeling Autonomous aerial vehicles Path planning Aircraft navigation Collision avoidance

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Manta Ray Foraging Optimization Approaches on Multivariable PID Controller Tuning

Manta Ray Foraging Optimization Approaches on Multivariable ...

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Congress on Evolutionary Computation

作者： Yan Lieven Souza Luúio Luiza Scapinello Aquino Da Silva Viviana Cocco Mariani Leandro Dos Santos Coelho Electrical Engineering Graduate Program (PPGEE) Federal University of Parana (UFPR) Curitiba Brazil Department of Electrical Engineering Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Brazil

This work presents a performance comparison between the newly developed Manta Ray Foraging Optimization (MRFO) and two different variants created for tuning a decentralized fractional order proportional-integral-derivative (FOPID) controller for a multiple-input multiple-output (MIMO) application. The application consists of a ball mill pulverizing system to pulverize coal and maximize fuel efficiency. MRFO and its applications have the task of finding the optimal controller variable values to control the system's temperature and pressure. The MRFO is a metaheuristic based on the behavior of manta rays, and although it shows efficient performance it may be improved through the use of techniques which generate new variants of the algorithm. Two techniques were used in the de-velopment of new variants: Quantum mechanics and opposition-based learning. The three different versions of MRFO were used to minimize a custom fitness function which is a combination of the integral time squared error (ITSE) and the overshoot of the system response. Simulations were carried using Simulink and Matlab softwares. For analyzing the performances, statistical measures such as minimum, maximum, best, mean, median, and standard deviation of the fitness function over 50 runs were used. Additionally, the different variants were also compared for minimizing 10 benchmark functions. The results show that the use of the previously mentioned techniques improve the performance of the original MRFO in optimizing the FOPID to control the ball mill pulverizing system.

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Multi-Objective Grey Wolf Optimizer for the Tuning Process of the FOPID Controller

Multi-Objective Grey Wolf Optimizer for the Tuning Process o...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Allan Christian Krainski Ferrari Gideon Villar Leandro Leandro Dos Santos Coelho Gilberto Reynoso Meza Eletrical Engineering Department Federal University of Paraná UFPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) Federal University of Paraná (UFPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná Curitiba Brazil

This article implements the multi-objective grey wolf optimizer (MOGWO) in the tuning process of the gains of the Fractional-Order Proportional-Integral-Derivative (FOPID) controller applied in the control of a boiler system. For a sequence of 100 runs, this application had compared and analyzed with other implementation that uses MOGWO to optimize the gains of the classical Proportional-Integral-Derivative (PID) controller. In the computational simulation, the value hypervolume metric had used to analyze the performance of the controllers. In the results, the implementation of the FOPID showed superior to PID, where the comparison had validated by a hypothesis test. Despite the higher computational cost concerning the tuning process of the PID controller, this study proved that the FOPID controller can be advantageous for industrial applications.

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An Online Application of Edge-Cloud Computing for Lithium-Ion Battery with SOC Estimation

An Online Application of Edge-Cloud Computing for Lithium-Io...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Joelton Deonei Gotz João Pedro dos Reis Mendes José Rodolfo Galvão Emilson Ribeiro Viana Fernanda Cristina Corrêa Milton Borsato Graduate Program in Mechanical Engineering (PPGEM) Federal Technological University of Paraná Curitiba-PR Brazil Graduate Program in Electrical Engineering (PPGEE) Federal Technological University of Paraná Ponta Grossa-PR Brazil Graduate Program in Physics and Astronomy (PPGFA) Federal Technological University of Paraná Curitiba-PR Brazil

The adoption of cloud and edge computing for several application motivates the monitoring and controlling a Lithium-ion batteries (LIB) online and remotely. In these scenarios, this work presents a case of study by the application of a hybrid concept of edge-cloud computing. The edge collects the data from the cells and sent directly to the cloud where several Machine Learning algorithms can be built, trained and tested. Then, the trained models are downloaded to the edge and do inferences in real time. The proposed idea presented still an SOC estimator based on Long Short-Term Memory (LSTM) with average error below 5%.

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Multi-Objective Grouped Grey Wolf Optimization of PID Controllers Applied to a Water Treatment Plant Model

Multi-Objective Grouped Grey Wolf Optimization of PID Contro...

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Congress on Evolutionary Computation

作者： Yan Lieven Souza Lúcio Viviana Cocco Mariani Leandro Dos Santos Coelho Electrical Engineering Graduate Program (PPGEE) Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil

A comparison of proportional-integral-derivative (PID) controller tuning for a 2x2 Multiple-Input Multiple-Output (MIMO) water treatment plant model is presented. The PID tuning procedures are based on Multi-Objective Grey Wolf Optimizer (MOGWO) and Multi-Objective Grouped Grey Wolf Optimizer (MOGGWO) are performed under two different initial conditions. The tuning procedure is structured as a multi-objective optimization problem with four objective functions, the integral time-squared error is minimized in each output response, and the integral of the control actions is minimized in each input. MOGWO is a metaheuristic based on the hunting behavior of grey wolves, following the hierarchy and leadership procedures that these animals have, while the proposed MOGGWO is a new version proposed in this study with two different groups with different functionalities. The performance was analyzed by 50 runs based on statistical metrics. MOGGWO can find more local minima since its Pareto front is more dispersed than that found by MOGWO.

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Online path planning for kinematic-constrained UAVs in a dynamic environment based on a Differential Evolution algorithm

arXiv

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arXiv 2024年

作者： Freitas, Elias J.R. Cohen, Miri Weiss Guimarães, Frederico G. Pimenta, Luciano C.A. Universidade Federal de Minas Gerais UFMG Graduate Program in Electrical Engineering Av. Antônio Carlos 6627 MG Belo Horizonte31270-901 Brazil Braude College of Engineering Karmiel Israel Universidade Federal de Minas Gerais UFMG Brazil

This research presents an online path planner for Unmanned Aerial Vehicles (UAVs) that can handle dynamic obstacles and UAV motion constraints, including maximum curvature and desired orientations. Our proposed planner uses a NURBS path representation and a Differential Evolution algorithm, incorporating concepts from the Velocity Obstacle approach in a constraint function. Initial results show that our approach is feasible and provides a foundation for future extensions to three-dimensional (3D) environments. © 2024, CC BY.

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Small Signal Modeling of DC-DC SEPIC Converter With Multilevel Flying Capacitor Switching Cell

Small Signal Modeling of DC-DC SEPIC Converter With Multilev...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Rhavél Batista Morais Montiê Alves Vitorino Jens Friebe Graduate Program in Electrical Engineering (PPgEE–COPELE) Industrial Electronics and Machine Drive Laboratory (LEIAM) Federal University of Campina Grande (UFCG) Kassel Germany Department of Power Electronics University of Kassel Kassel Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Nowadays multilevel converters have been widely adopted in low and medium power DC-DC conversion systems, especially for automotive applications and renewable energy systems. However, the increase in the number of components and the complexity of the control also complicate the modeling and control of these converters. A dynamic model will be detailed, studied, and used to illustrate the properties of the SEPIC DC-DC converter with three-level flying capacitor switching cell. The model’s applications include, but are not limited to, controller analysis, design for load voltage regulation, and flying capacitor voltage balancing. Both simulations and experimental results are provided to verify the principle of operation.

关键词： Renewable energy sources Multilevel converters Capacitors Prototypes Switches Voltage control Integrated circuit modeling Vehicle dynamics Load modeling Switching circuits

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CAN-Modes: In-vehicle datasets generation and analysis in different driving situations

CAN-Modes: In-vehicle datasets generation and analysis in di...

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Workshop on Communication Networks and Power Systems (WCNPS)

作者： Alexandre Dos Santos Roque Lucas Melo Da Silva Alves Edison Pignaton de Freitas Regional Integrated University of High Uruguay and Missions - URI Santo Angelo RS Brazil Graduate Program of Electrical Engineering (PPGEE) Federal University of Rio Grande do Sul (UFRGS) Porto Alegre RS Brazil

ISBN: (数字)9798331507152

ISBN: (纸本)9798331507169

In-vehicle networks are responsible for safety-critical control applications, depending on data communication between electronic control units, and most are based on the CAN protocol. A huge amount of data is necessary for reliability, safety, and cybersecurity analysis in today's automotive solutions, especially to feed machine learning models. It is relevant to provide comprehensive datasets about CAN communication and different driving situations, which represents a lack in recent research because most public datasets are very limited. This paper addresses this problem by providing a set of CAN datasets collected in real cars and driving conditions, analyzed, and preprocessed for further research applications. The results present data collection and labeling, in three car brands, two data types (RAW and OBD pids), and they are available in recognized public sources.

关键词： Protocols Machine learning Data models Safety Power system reliability Automobiles Reliability Labeling Feeds Data communication

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Mathematical Analysis and Space Vector Modulation of the Three-phase Buck-Boost Rectifier with Reactive Power Capability

Mathematical Analysis and Space Vector Modulation of the Thr...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Yan Pontes Figueiredo Montie Alves Vitorino Jens Friebe Graduate Program in Electrical Engineering (PPgEE-COPELE) Industrial Electronics and Machine Drive Laboratory (LEIAM) Federal University of Campina Grande (UFCG) Campina Grande Brazil Department of Power Electronics University of Kassel Kassel Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Buck-boost current-source based converters are attractive for applications in electric vehicles (EVs) due to several inherent benefits regarding high-power charging. However, methods are still needed to increase the efficiency of these converters. This paper covers a mathematical analysis of the three-phase buck-boost rectifier with reactive power capability and shows its equation and operating conditions for a wide range of power factors. In addition, the control strategy based on space vector modulation (SVM) is presented in detail, as well as the passive elements design. Experimental results show that the converter modulated by SVM is more efficient in terms of switching losses compared to scalar modulation.

关键词： Support vector machines Reactive power Mathematical analysis Modulation Rectifiers Switching loss Energy conversion Aerospace electronics Electric vehicles Vectors

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