Mestrado em Engenharia Elétrica
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- ItemFornecimento ótimo de serviços ancilares por parte de geradores distribuídos em sistemas de distribuição de energia elétrica(Universidade Federal do Espírito Santo, 2025-10-20) Nascimento, Daniel Fonseca do; Rueda Medina, Augusto César ; https://orcid.org/0000-0002-4291-3153; https://lattes.cnpq.br/7397584412509839; https://orcid.org/0009-0006-6730-7527; https://lattes.cnpq.br/3412161686902841; Santos, Walbermark Marques dos ; https://orcid.org/0000-0002-9871-6028; https://lattes.cnpq.br/5558697161842579; Ferraz, Rafael Santos Freire ; https://orcid.org/0000-0001-8857-011X; https://lattes.cnpq.br/5323068276181437The increasing penetration of DG units, particularly photovoltaic systems, has transformed the operation and planning of distribution networks, opening opportunities for these resources to provide complementary functions such as reactive power support, voltage regulation, and active power reserve for frequency control. This dissertation thesis investigates the provision of ancillary services (AS) through distributed generation (DG) in electric power distribution systems, emphasizing the technical, economic, and regulatory aspects that determine the feasibility of this application. To assess this potential, a market-based dispatch methodology was developed and implemented in the optimization environment AMPL, considering operational constraints and compliance with voltage quality standards established in Module 8 of the Brazilian Distribution Procedures. The methodology was applied to the IEEE 37-bus test feeder in a 24-hour simulation, optimizing the active and reactive dispatch of DG units. The technical results highlight improvements in voltage profiles, mitigation of violations beyond the Permitted Deviation Range and Critical Deviation Range, and reduction of power losses. From an economic perspective, the model demonstrates significant benefits for distribution utilities, including a 41% reduction in system operating costs and a 93.5% decrease in regulatory penalty expenses related to non-compliance with service quality limits. Additionally, the study incorporates a competitive market remuneration structure, analyzing how such a mechanism can incentivize DG participation based on actual operational costs. The findings suggest that DG-based AS provision is both technically feasible and economically advantageous, enhancing system robustness, encouraging efficiency, and improving regulatory performance indicators of continuity and power quality. These results reinforce the relevance of integrating DG into ancillary service frameworks as a strategic approach to modernize distribution systems, align with regulatory requirements, and promote a more resilient and sustainable electricity sector
- ItemControle preditivo baseado em modelo com restrições flexíveis para rastreamento de trajetória e desvio de obstáculos em VANTs(Universidade Federal do Espírito Santo, 2025-12-11) Laura, Diego Abraham Apaza; Villa, Daniel Khede Dourado; https://orcid.org/0000-0002-8345-5590; https://lattes.cnpq.br/7020533470048010; https://orcid.org/0000-0001-9567-8954; https://lattes.cnpq.br/7628820433240540; Celeste, Wanderley Cardoso ; https://orcid.org/0000-0002-1121-937X; https://lattes.cnpq.br/3919161245148947; Salles, Jose Leandro Felix ; https://orcid.org/0000-0002-3417-6544; https://lattes.cnpq.br/1368496315730875; Carvalho, Kevin Braathen de ; https://orcid.org/0000-0003-3639-8826; https://lattes.cnpq.br/1918730771175641This dissertation presents the design, implementation, and experimental validation of a Model Predictive Control (MPC) framework for trajectory tracking and obstacle avoidance in Unmanned Aerial Vehicles (UAVs) of the quadrotor type. The strategy focuses on safe navigation in dynamic environments. The core of the approach consists of an avoidance mechanism that linearizes the non-convex collision constraints at each step of the prediction horizon using time-varying tangent planes. This allows the optimization problem to be efficiently formulated and solved as a standard Quadratic Program (QP). To enhance robustness and ensure solver feasibility in highly constrained scenarios or in the presence of disturbances, the optimization problem incorporates flexible constraints. This technique uses slack variables to allow temporary violations of safety zones at a high penalty cost, ensuring a feasible solution is always found. The controller was implemented in MATLAB and executed on a ground station, communicating with the UAV in real-time (30 Hz) via the Robot Operating System (ROS). Validation experiments were conducted using a real quadrotor (Parrot Bebop 2), whose pose was provided by a motion capture system (OptiTrack). Test scenarios included trajectory tracking and setpoint regulation in the presence of multiple static and dynamic obstacles (Pioneer 3-DX ground robots). The results demonstrate that the proposed system enables the UAV to navigate efficiently and smoothly, anticipating and executing safe evasive maneuvers. The successful completion of all experimental scenarios validates the effectiveness and reliability of the approach for safe operation in complex environments.
- ItemDevelopment of an optical force sensor: a novel approach for monitoring physical interaction in robotic walkers(Universidade Federal do Espírito Santo, 2026-02-20) Garcia Alvarez, Daniel Eduardo; Frizera Neto, Anselmo; https://orcid.org/0000-0002-0687-3967; https://lattes.cnpq.br/8928890008799265; Múnera Ramirez, Marcela Cristina; https://orcid.org/0000-0001-6595-5383; https://lattes.cnpq.br/0934278112355648; Rodríguez Díaz, Camilo Arturo; https://orcid.org/0000-0001-9657-5076; https://lattes.cnpq.br/2410092083336272; https://orcid.org/0000-0002-5491-660X; https://lattes.cnpq.br/9190745277681587; Silveira, Mariana Lyra; https://orcid.org/0000-0002-0368-5629; https://lattes.cnpq.br/5307116832176112; Lima, Eduardo Rocon de; https://orcid.org/0000-0001-9618-2176This dissertation presents the design, development, and experimental validation of an optical sensor (OS) for monitoring interaction forces in smart walkers (SWs). The proposed sensing approach integrates light-sensitive photodiodes and addressable RGB light-emitting diodes embedded within a compliant encapsulation material, enabling force estimation by measuring changes in optical signals caused by surface deformations. Compared to conventional force-sensing technologies (i.e., strain gauges, piezoelectric sensors, and high resolution triaxial force cells) and optical Ąber-based alternatives (i.e., polymer optical Ąbers and Ąber Bragg gratings), the proposed OS reduces system complexity while ofering a cost-efective and easily manufacturable design, facilitating its integration into SWs. The Ąrst OS prototype validated the feasibility of the proposed approach, achieving an average force estimation error of 2.4%. Meanwhile, it identiĄed contact zones with an accuracy of 98%. These results demonstrate reliable performance in both force regression and contact localization, as well as the ability to capture the spatial distribution of applied forces. A second development stage focused on a redesigned OS geometry optimized for walker-handle integration, enabling force sensing across multiple interaction zones. An evaluation of the efects of encapsulation materials and illumination wavelengths on OS performance revealed that combination of EcoĆex encapsulation and red light provided the best results, achieving the lowest mean squared error (MSE) (Validation: 4.72 ± 0.31; Test: 4.96), mean absolute error (MAE) (Validation: 1.61 ± 0.04; Test: 1.79), and the highest coeicient of determination (R2) (Validation: 0.98 ± 0.01; Test: 0.97). The optimized conĄguration also demonstrated good generalization to unseen loads, with an average error of 5.56%. To assess repeatability, four new OS units implementing the optimized conĄguration were fabricated and independently calibrated. Among them, the fourth OS achieved the best results, with the lowest prediction errors (MSE validation: 3.11 ± 0.55; test: 3.33; MAE validation: 1.18 ± 0.10; test: 1.24) and the highest correlation values (R2 validation: 0.98 ± 0.02; test: 0.98). Validation against a commercial reference system conĄrmed estimation errors below 5.78% across all four OSs. Finally, the integration of the OSs into a SW and their evaluation during path-following trials with ten healthy participants demonstrated consistent force redistribution patterns across straight and turning maneuvers, highlighting the sensorŠs capability to capture meaningful interaction dynamics in real-world scenarios. Overall, this work demonstrates that waveguide-based OS combined with data-driven models constitutes a robust, scalable, low-complexity, and cost-efective solution for estimating interaction forces in SWs.
- ItemDetecção de transtorno mental via EEG, microestados e redes neurais de grafos(Universidade Federal do Espírito Santo, 2025-05-27) Candeia, Daniel Ribeiro; Ciarelli, Patrick Marques ; https://orcid.org/0000-0003-3177-4028; http://lattes.cnpq.br/1267950518719423; https://orcid.org/0009-0001-4427-7496; http://lattes.cnpq.br/2696632870728316; Côco, Klaus Fabian ; https://orcid.org/0000-0001-7793-0693; http://lattes.cnpq.br/1374499533178055; Tello, Richard Junior Manuel Godinez ; https://orcid.org/0000-0003-1428-0990; http://lattes.cnpq.br/3966230569744918Electroencephalogram (EEG) is a non-invasive and cost-effective technique widely used to study brain activity and diagnose neurological disorders. However, visual analysis of EEG signals is complex and requires expertise, highlighting the need for automated diagnostic support systems. In this context, this study proposes a graph-based neural network model for detecting mental disorders using EEG signals, leveraging microstate analysis. The proposed model integrates graph neural networks (GNNs) with microstate analysis, which captures transient and stable patterns of brain activity. The TUH Abnormal EEG Corpus (TUAB) dataset, containing normal and abnormal EEG signals, was used. The process included the extraction of microstates, the construction of graphs based on Spearman correlation between EEG channels, the extraction of features from EEG signals, and the application of Principal Component Analysis (PCA) to reduce the dimensionality of these features. Three GNNs were trained, each associated with signals from each microstate, and their outputs were combined using an ensemble technique. The final model achieved an accuracy of 97.46% on the test set, outperforming existing results of methods in the literature. The results highlight the effectiveness of the proposed approach, demonstrating the potential of GNNs and microstate analysis for detecting mental disorders from EEG signals
- ItemDevelopment of a mobile service robot system: enhancing localization, guidance, and search tasks in indoor environments(Universidade Federal do Espírito Santo, 2025-08-06) Rodriguez, Elio David Triana; Jiménez-Hernández, Mario Fernando ; https://orcid.org/0000-0003-0965-277X; http://lattes.cnpq.br/6078067029625341; Frizera Neto, Anselmo; https://orcid.org/0000-0002-0687-3967; http://lattes.cnpq.br/8928890008799265; https://orcid.org/0009-0000-4454-987X; ttp://lattes.cnpq.br/3696912600039873; Santos, Thiago Oliveira dos; https://orcid.org/0000-0001-7607-635X; http://lattes.cnpq.br/5117339495064254; Avilés Sanchez, Oscar Fernando ; https://orcid.org/0000-0001-8676-9926; http://lattes.cnpq.br/7481150993160615Advancements in service robotic systems demand robust Human-Robot Interaction (HRI) strategies capable of operating in multilingual and dynamic environments. However, current HRI approaches based on Natural Language Processing (NLP) often face limitations related to scalability, ambiguity in communication, and dif f iculty in linking unstructured input to structured data, thereby reducing robotic adaptability. This study proposes an HRI framework that integrates NLP through Large Language Models, combined with a decision-making algorithm grounded in Generative Artificial Intelligence (Generative AI) and context-aware reasoning. The system adopts a modular architecture comprising request validation, map valida tion, and response generation, enabling the synthesis and association of structured andunstructured data. As a result, the robot is capable of navigating, guiding users, executing adaptive tasks, and responding to user requests through a chat-style in terface. The framework was implemented on a mobile robot that was structurally, electrically, and software-wise adapted, culminating in the development of an au tonomous system able to complete localization, guidance and search tasks in in door environments. The NLP-based interaction modules were then integrated, and the resulting autonomous responses to user requests were evaluated as satisfactory. Usability evaluations conducted with real users, using the System Usability Scale (SUS), yielded consistently high scores ranging from “good” to “excellent.” How ever, participants reported a slightly lower perception of accuracy and increased frustration when operating in fully autonomous LLM mode compared to a pre programmed control mode. On the other hand, validation experiments demon strated a 91% success rate, confirming the system’s capability to process user re quests andexecutetaskstypicalofguiderobots. Theseresultsvalidatethefeasibility of integrating LLMs into multilingual robotic systems, highlighting both the poten tial and current limitations of NLP in HRI. They also highlight the transformative role of LLMs in enhancing natural language understanding and decision-making in real-world scenarios. Future work should focus on improving the handling of ambiguous user requests and refining feedback mechanisms to enhance the overall user experience.