Theses (Department of Electrical Engineering and Mechatronics)
Állandó link (URI) ehhez a gyűjteményhez
Theses collection of the Department of Electrical Engineering and Mechatronics. The collection was started in 2023.
At the University of Debrecen, in accordance with the 2022 amendment to the 2011 Higher Education Act, student theses are only accessible from devices connected to the University's Eduroam WiFi network or from a university IP address.
“The thesis or diploma work of a student who has successfully passed the final examination shall be stored in full in the academic system of the higher education institution, and a record shall be maintained thereof. The stored theses and diploma works – with the exception of parts classified as confidential in accordance with the relevant legislation – must be made accessible and searchable without restriction through the academic system.” Further info on the National Higher Education Act in Hungarian: Felsőokt. tv. (új) - 2011. évi CCIV. törvény a nemzeti felsőoktatásról - Hatályos Jogszabályok Gyűjteménye.
Böngészés
legfrissebb feltöltések
Megjelenítve 1 - 20 (Összesen 120)
Tétel Embargó alatt mobile robot navigation algorithm with reinforcement learning method enhanced.Gmar, Ghofrane; Taleb abdullah abdo, Mayar; DE--Műszaki KarThis thesis studies the challenges of mobile navigation in a dynamic environment. In this thesi,s different categories of algorithms (graph-based, sample-based,...) are tested in static and dynamic environments to study their functionality, and then finally, I integrate reinforcement learning and potential field methods for mobile navigation enhancement. The final navigation approach is a hybrid approach that consists of a global planner( Hybrid A*and D*lite), a local planner( Q-learning and potential field method). The global planner provides the robot with a pre-defined path based on the given map and the local planner helps the robot to react in real-time to unexpected changes in the environment. The hybrid approach is a more stable and adaptable method, although it should be refined to ensure stability and consistency in performance.Tétel Korlátozottan hozzáférhető Optimization of Path Planning Algorithms for Autonomous Navigation in Simulated and Real EnvironmentsHakiri, Mohamed Amine; Husam , A. Neamah; DE--Műszaki KarThis works presents an in-depth performance comparison of path planning algorithms for autonomous mobile robot navigation under simulated and real environment. Five different navigation strategies were systematically contrasted: four planner combinations of A * and RRT* with DWA, TEB and an end-to-end (E2E) policy trained from scratch based on the Proximal Policy Optimization algorithm. The evaluation was performed on a home-made robot with differential drive kinematics, an RP LIDAR A1M8 laser scanner, an Arduino based module, and a Raspberry Pi 4 in indoor warehouse like scenarios. The experimental procedure consisted of several test situations using three different target locations in static and dynamic obstacle environments. Each configuration was executed three times for robustness, which is crucial in the context of probability-based RRT. Performance was assessed using multiple metrics including the number of calls to global planner representing replanning rates, time to reach goal, and for RRT – failed attempts at path generation. Experiments were done in simulation with Gazebo and the results was verified on the real robot. Simulation results indicated that A*-based combinations counted less replanning calls in comparison with RRT-based, and A+TEB, realized the best calculation time when operating in static environments. In dynamic obstacle environment, local planner decision played a more important role than the global planner selection. RRT had a find failure rate of 15% at the end of their used computation time, and A* found paths in case such exist. The exploratory analysis using deep reinforcement learning also demonstrated good performance but computing resources were demanding. System level validation showed reasonable real-world transfer of simulation results to the physical system, albeit with different absolute performance indicators due to sensor noise and wheel slip. The results give practical advice for choosing an algorithm depending on the application requirements, for instance on the complexity of the environment and computational resources available or desired level of reliability. The primary contribution of this paper is to make available empirical data that help practitioners select navigation algorithms suitable for various settings in mobile robot applications.Tétel Embargó alatt 3-phase BLDC motor analysis and control using Tensor Product TransformationAttia, Youssif Attia Aly; Taleb, Mayar; DE--Műszaki KarThis thesis designs and tests an angle-scheduled tensor-product (TP) state-feedback controller for speed control of a three-phase BLDC motor, modelled as an LPV system whose matrices depend on electrical rotor angle. The angle dependence is approximated by a 12-vertex polytopic model, and vertex gains are computed via LMIs with a common quadratic Lyapunov function; in real time the controller interpolates these gains and applies rate-limited, saturated phase voltages through a PWM interface. In nonlinear Simulink simulations of a 0–3000 rpm step, the TP and composite PI+TP controllers achieve 5–6 ms rise time, 10–15 ms settling time and 3–4% overshoot, whereas a tuned PI loop shows similar rise time but about 12% overshoot and ~45 ms settling. Steady-state results show that PI and PI+TP have essentially zero error and negligible ripple, while pure TP leaves a small bias and ~75 rpm peak-to-peak ripple, so the PI+TP architecture is identified as the best compromise between fast dynamics and smooth steady state.Tétel Embargó alatt Vision Based Automated optical inspection for real time quality controlNegm, Shahd; Taleb, Mayar; DE--Műszaki KarThe thesis presents a compact, low-cost, vision-based inspection and rejection cell for mixed SKU household chemical bottling lines operating at realistic conveyor speeds. A single fixed-view USB camera with controlled ring light illumination and a matte background feeds a modular perception pipeline that performs SKU aware localisation, cap height profiling, label and color verification, expiry date OCR and silhouette based deformation analysis. A lightweight YOLOv8 detector provides robust bottle level region proposals, while physics based geometric measurements and rule based checks are used for the individual quality tasks instead of an end to end black box network. Per bottle decisions are converted into a binary reject signal for a PLC controlled electropneumatic pusher, with timing budgets derived analytically from conveyor flight distance, image processing latency and actuator dynamics to guarantee correct removal of defective units. Experiments on representative bottle types show perfect cap sealing classification and competitive performance on the other tasks, including 97.0% accuracy for deformation detection, 90.9% for label conformity and 87.9% for expiry code recognition using only commodity imaging hardware and open source software. The work demonstrates a practically validated, retrofittable AOI solution that combines modern deep learning with interpretable geometric features and structured data logging, and is therefore well suited to Quality 4.0 upgrades in small and medium sized bottling plants.Tétel Korlátozottan hozzáférhető Optimal Control Design-based Grey Wolf Optimization Algorithm for Suspension System in Electric VehicleAbdurrahman, Faisal Haruna; Babangida, Aminu; DE--Műszaki KarThis research focuses on improving electric vehicle suspension systems using optimal control design based on Grey Wolf Optimization (GWO). It integrates a PID Controller, optimized by the GWO algorithm, with a passive suspension system to better handle road disturbances. The goal is to enhance ride comfort and maintain consistent road-wheel contact by reducing the impact of surface irregularities. Additionally, the study compares the performance of the GWO-PID system with a Model Predictive Contol (MPC) system. The comparison is evaluated using the Integral-Time weighted Absolute-Error (ITAE) as the fitness function.Tétel Korlátozottan hozzáférhető Kinematic simulation of a FANUC CRX 10iA/L collaborative robot in Simscape Multibody environment for motion analysisHumphery, Rosemary Chiemerie; Korsoveczki, Gyula; DE--Műszaki KarGiven the state of technology, the field of robotics is developing into where humans and robots share workspaces. As a result, human and robots have been able to work side by side due to this new emerging robotic system known as COBOT. This paper deals with the motion simulation of FANUC collaborative robot in Simscape Multibody for performance evaluation. By integrating the kinematic and dynamic parameters into the FANUC cobots I will be able to visualize how it behaves in the virtual environment. I will be using the FANUC CRX 10ia/l for the simscape multibody physics-based modelling, various trajectories and payload that are associated with each joint. This simulation done in MATLAB enables a detailed performance of the robot in terms of accuracy, repeatability and so on. The simulation results also shows valuable insights into the capabilities of the robot’s motion and reachability, which can be used for path planning, trajectory optimization, control system development, industrial applications, and educational purposes. With the use of this prototyping, we can use cobots in industries in a safe and effective way.Tétel Korlátozottan hozzáférhető Kinematic analysis and singularity avoidance of a SCARA robotMoqbel, Oday Abdulrakeeb Ali; Vígh, Dániel; DE--Műszaki KarThis thesis presents a Modeling and Control framework for a Four-DOF SCARA Manipulator in an RRPR joint configuration. It provides both Analytical Kinematics and Weighted Least-Squares Inverse Kinematics; along with Joint Space PID Control in the MATLAB Simulink and Simscape Multibody environments. Forward kinematics are represented by Denavit-Hartenberg transformation matrices that map joint coordinates to Cartesian coordinates (Position and Orientation) of the End-Effector. Closed form equations for Inverse Kinematics are used to determine planar joint coordinates from geometric relationships between links, while the prismatic joint determines Vertical Positioning and the Wrist Joint determines Tool Orientation. A Weighted Least-Squares Method with variable weights and Tikhonov Damping has been used to provide Stability near Singularities. Simulation Results indicate accurate Path Tracking and Stable Joint Motion; thus validating both the Kinematic Models and the PID Control.Tétel Korlátozottan hozzáférhető Control of a pneumatic and stepper motor driven TTT machineAbzakh, Omar Ashraf Burhan; Mikuska, Róbert; DE--Műszaki KarThis thesis project presents the rehabilitation and modernization of a three-axis TTT Machine that utilizes a hybrid actuation system made of pneumatic cylinders and a stepper motor that is equipped with an encoder. The machine which was previously used for automation demonstrations in the faculty, had resided in the robotics lab in a semi-assembled state after its relocation. This project’s ambition was to restore full functionality of the system through reverse engineering, careful reassembly, and control optimization using PLC based architecture. The main problems that are addressed include unclear physical wiring that has a lot of floating disconnected wires which made it hard to understand what element is connected to what other element, and a lot of relying on open loop control and lack of measurement data, coupled with some challenges in unifying the software experience to make all aspects of the machine observed and controlled from the same software. The steps towards finalizing this task involves detailed component analysis, integration of reliable sensor data and implementation of PLC control logic to control and measure the output of controlling the machine and enhance system performance. The outcome of this study is a reengineered TTT machine, where the pneumatic axles were renovated to up-to-date automation technology with improved test repeatability, control accuracy providing a good foundation for future automation experiments and educational purposes.Tétel Korlátozottan hozzáférhető Smart University LaboratoryAwad, Noureldin Elsadig Hassan; Almusawi, Husam Abdulkareem; DE--Műszaki KarThis thesis describes the design, programming, implementation of a complex Smart Electrical University Laboratory System, a single digital environment which is configured to transform the management of laboratory by overcoming the slowness of the conventional paper-based processes. The hybrid architecture of the system is its key innovation: The Smart Inventory System and Face Recognition Attendance System are implemented as a secure web-based application that runs locally over the Wi-Fi network of the lab and allows comfortable and device-independent access to all smartphones, tablets, or computers located inside the lab and the data privacy of the system is ensured by the lack of contacts with the world as well as by the absence of service usage on cloud systems. Conversely, both the Voice Assistant and Lab Schedule Manager are native host applications , and use its increased processing power to perform real-time, resource-intensive tasks, audio processing, and the ability to serve a PyQt5-based GUI-rendering to the display, functions that could not be performed on the original Raspberry Pi 3 because of the extreme limitations in memory and processing power. Facial Recognition system FaceNet, which is developed with a small CNN model (FaceNet) through DeepFace, offers high-precision, low-latency recognition in controlled lab conditions, and the system has high-quality error recovery algorithms. The smart integration is another strength factor that improves resiliency of the system: the voice assistant offers contextual technical support, where speech requests are dynamically integrated in the inventory system interface, and the attendance data is automatically aligned with the inventory activities to monitor the equipment usage. The Lab Schedule Manager is an independent Pi 4 application that offers a powerful real-time scheduling interface that allows access to the lab table and laboratory sessions with no conflicts using a dedicated desktop application. This design with a centralized data storage and user interface through a secure and open web interface and delegated real-time and high-load tasks to host applications in the Pi 4 provides a scalable, reliable, and economical ecosystem. The development plan was focused on realism and stability: the complete system was initially created, debugged and tested on a Windows PC to fix the complicated Python library incompatibility issues and to guarantee the functionality. This was then put into final code that was fully tested and optimized and run on Raspberry Pi 4, thereby proving its feasibility on current embedded hardware. The three-pronged method of development of windows, deployment on Pi 4 and accessing the system to a secure web interface makes sure that the system is not only technically sound but accessible to all users, secure and practical.Tétel Korlátozottan hozzáférhető ADAPTIVE STATE SPACE CONTROL FOR EV POWERTRAINMansour, Abdelrahman Waled Ali Mahmoud Ali; Károly Árpád, Kis; DE--Műszaki KarThis project presents the design of an adaptive speed control system for a permanent magnet synchronous motor for electric vehicle applications. The MRAC approach is used to achieve robust performance for wide-ranging load conditions and system uncertainties. In the controller design, a reduced-order PMSM model is considered, considering the main vehicle dynamics and external resistive forces such as aerodynamic drag, rolling resistance, and road grade effects. Simulations are executed stepwise, from pure force applications to combined load conditions. Further, performance is validated on two standard drive cycles: FTP-72 and HWFET, for urban and highway driving conditions. The results depict accurate speed tracking, stable current regulation, and robust adaptability to dynamic torque demands. The MRAC-based controller has been effective in ensuring performances over a wide envelope of operating conditions, thus laying a very good platform for further improvements in intelligent EV control systems.Tétel Korlátozottan hozzáférhető Design and implementation of a real-time plc-controlled elevator system with HMI integration and stage-based optimization using CODESYSBader, Abdallah Ibrahim Jamil; Vígh, Dániel; DE--Műszaki KarThe proposed thesis provides an excellent structure to present a complete and structured investigation into the design and simulation of a plc controlled five-floor good-lifts systems based upon the codesys-platform. This study clearly displays a strong technological base for integrating different sub-systems (motion control, door operation, sensors and hmi) for the PLC. The inclusion of both an automated mode and manual operating mode combined with all the security functions needed for safe use show how this system can be practically used. The description of the simulation is also very clear and shows that the developed control logic is reliable and responsive. In general the thesis demonstrates that the presented solution fulfills the required functionalities and safety demands and therefore validates the application of virtual prototype development for the creation of Industry 4.0-compliant automation systems.Tétel Korlátozottan hozzáférhető Design and Implementation of a ROS 2-Based Autonomous Driving System in a Simulated EnvironmentAwadelkarim, Ahmed Adil Ali; Mikuska, Róbert; DE--Műszaki KarThe main objective of this thesis was to develop a modular perception and control system for autonomous vehicles, as well as validate it via testing in a realistic simulation environment (Gazebo/ROS), utilizing Ackerman steering kinematics. The primary focus of the research was to achieve robust real-time autonomous navigation on complex simulated tracks through the integration of computer vision and robotics. A central focus of the research was the Hybrid Computer Vision Pipeline, which provides the ability to balance high accuracy and computational efficiency for the vehicle. For lane-following, the system utilized fast heuristic methods, specifically HSL Color Segmentation and Canny Edge Detection to provide the vehicle's geometric data (e.g., curvature). Traffic sign detection was accomplished through a multi-step process consisting of Hough Gradient Methods and Haar Cascades to quickly localize signs, then a custom CNN to accurately classify them. Overall, the research demonstrated the critical tradeoff between efficiency and reliability in achieving electric mobility automation.Tétel Korlátozottan hozzáférhető MOBILE ROBOT FOR NAGIVATION AND OCCUPANCY GRID MAPPINGBello, David Oluwasegun; Abdulkareem Almusawi, Husam; DE--Műszaki KarThe aim of this thesis to implement a mobile robot to deliver packages in an enclosed space: remotely to a recipient. This can be applied in various fields such as health care systems in hospitals, transportation and delivery of goods and packages. The robot uses Extended Kalman Filter for sensor fusion. Bayes Theorem was used to update the cells in the occupancy grid map made in real time Simultaneous Localization and Mapping. Bresenham algorithm acts as a checker between the robot and obstacles to detect the presence of free space that the bayes theorem updates with log-odds. The navigation uses frontier based as the robot explore the environment while performing SLAM. The navigation used is after the map has been built is DWATétel Korlátozottan hozzáférhető Building self-rotating solar panel for sun tracking to optimize power outputShehata, Ahmed; Vígh, Dániel; DE--Műszaki KarThis thesis presents the design, development, and testing of a dual-axis self-rotating solar panel system aimed at optimizing photovoltaic energy output through automatic sun tracking. By integrating low-cost components such as LDR sensors, a Raspberry Pi 5, and servo motors, the system continuously adjusts the panel’s orientation to face the sun perpendicularly. The control algorithm, written in Python, ensures real-time responsiveness and improved efficiency over fixed-panel systems. Experimental results demonstrate a significant increase in energy output, ranging between 25% and 45%. The study also includes economic analysis, highlighting the system’s cost-effectiveness despite higher initial investment. Overall, the thesis illustrates a practical and scalable solution to enhance renewable energy utilization through automation and intelligent tracking technology.Tétel Korlátozottan hozzáférhető Decentralized Coordination and Control of Mobile Robot Swarms for Autonomous Task ExecutionSelenge, Ganbat; Almusawi, Husam; DE--Műszaki KarMulti-robot systems offer significant advantages over single-robot approaches in terms of adaptability, fault tolerance, and efficiency. However, a primary challenge in deploying low-cost robot swarms is maintaining accurate localization over time, as reliance on low-cost proprioceptive sensors (wheel encoders and IMUs) leads to accumulated odometry drift. Equipping every agent with high-precision environmental sensors and sufficient computing power for Simultaneous Localization and Mapping (SLAM) effectively solves this issue but negates the cost effectiveness and scalability of the swarm. This thesis presents the design, implementation, and evaluation of a cooperative localization framework within the Robot Operating System 2 environment. The system uses a heterogeneous "Leader Follower" architecture to address trade-off between localization accuracy and system cost. The architecture designates a single, computationally capable "Leader" robot equipped with a 2D LiDAR to function as a mobile perception hub, while "Follower" robots rely on minimal onboard sensing. The methodology integrates three core technical components: Global Perception, Relative Tracking, and Sensor Fusion. The framework was validated using a high-fidelity physics simulation in Gazebo. Real life hardware framework has been developed. Experimental results compare the trajectory accuracy of Followers relying solely on dead reckoning against those corrected by the cooperative system. The analysis demonstrates that the implemented framework reduces localization error, effectively mitigating sensor drift and enabling stable formation control without requiring expensive sensors on individual Follower units. This work confirms the viability of LiDAR based relative tracking for low-cost swarm coordination in GPS-denied environments.Tétel Korlátozottan hozzáférhető Design and Development of an Automated Dual Station Robotic Welding Station to use in Forklift Cabin AssemblyAlmulla, Yousif; Korsovecki, Gyula; DE--Műszaki KarThe project describes the configuration, manufacture, and deployment of a fully automated robotic welding carrier to join sub-entities of tractor cabs. It consists of a KUKA industrial robot and a Fronius welding system integrated into the cell that is synchronized over a ProfiNet industrial network. Its major characteristics are the two servo-controlled positioners used in manipulating the parts, the centralized control with the usage of a Siemens PLC, and an elaborate safety system, which includes scanners of the areas. Automated functions included in the system are the cleaning of the torches after each time and the automatic recalibration of the tool center point (TCP) after the collisions. The application proves to be a strong, secure, and effective assembly of industrial welding, which is highly precise with the least level of operator involvement.Tétel Korlátozottan hozzáférhető Simulation-Based Development of Quadcopter Dynamics and ControlRadec, Milica; Kis, Károly Árpád; DE--Műszaki KarUnmanned Aerial Vehicles (UAVs), particularly quadcopters, have seen an explosion in use, yet their nonlinear, coupled, and underactuated dynamics make control a challenging problem. This thesis presents a comprehensive simulation-based platform developed in MATLAB to model quadcopter flight dynamics and evaluate control strategies without the risks of hardware testing. A physically accurate nonlinear mathematical model was derived, incorporating rigid-body dynamics, motor response, and environmental disturbances. Two control architectures, a cascaded PID controller and a Linear Quadratic Regulator (LQR), were designed and subjected to comparative analysis under nominal and disturbed conditions. Results demonstrate that while PID provides baseline stability, the LQR controller offers superior trajectory tracking, robustness, and disturbance rejection. This work establishes a validated framework for future advanced control development and hardware integration.Tétel Korlátozottan hozzáférhető STABILIZATION OF A QUADCOPTER USING PID CONTROL AND METAHEURISTIC ALGORITHMSMOKORO, PAUL; SANDOR, HAJDU; DE--Műszaki KarThis thesis focuses on quadcopter stabilization using PID control enhanced with metaheuristic optimization methods. A mathematical model of the quadcopter was developed in MATLAB and Simulink to support controller design. Classical PID tuning methods and metaheuristic optimisation methods were tested and shown to produce overshoot, slow settling and limited robustness. Simulation results indicated that Grey Wolf Optimization achieved the best results in response speed and overshoot reduction. The results were further validated in the Webots 3D environment under hovering, trajectory tracking and disturbance scenarios. These results confirm that metaheuristic tuning significantly enhances quadcopter stability.Tétel Korlátozottan hozzáférhető Design of an EMG-sensing prosthetic armMbirimujo, Nokokure Christoph; Almusawi, Husam Abdulkareem; DE--Műszaki KarThe thesis presents the design and development of a low-cost, EMG controlled prosthetic arm that uses a scotch yoke mechanism as a driving system. The scotch yoke converts rotary motion into precise linear motion for the finger movement. The entire arm is 3D using PLA, enabling rapid prototyping, weight reduction and customization. A kinematic and FEA analysis was conducted to validate the mechanical design and structural integrity. Preliminary testing showed that EMG signals could control the opening and closing of the prosthetic. While functional, the current prosthetic arm has limitation in actuator stability and lacks a user socket.Tétel Embargó alatt OPTIMIZATION AND CONTROLLING OF BIONIC ARM USING ELECTROMYOGRAPHY (EMG) SIGNALRaseela, Rafeeq; Almusawi Abdulkareem, Husam; DE--Műszaki KarThe loss of an arm significantly impacts a person’s independence and a struggle to perform the daily activities. Bionic prosthetic arm has been life-changing for these people. The introduction to various control strategies such as Electromyography (EMG) has transformed the bionic arm by making it functional, responsive and precise. This thesis mainly focuses on the EMG as control strategy which helps people to control the myoelectric arm with muscle intention just like a normal arm. The EMG signals from the sensors, SHIMMER EMG and Arduino Myoware, are captured using software MATLAB and Arduino IDE. These signals are later processed and used to control the gesture of the arm using the same software. The study focused on EMG signals from the forearm muscles such as Extensor digitorum and Flexor carpi radialis for training the model using the MATLAB Toolbox. The training includes simple hand gestures such as hand open, hand close and flexion of all five fingers individually. Feature Extraction performed for time-domain features such as the Root Mean Square (RMS), Mean Absolute Value (MAV) and Waveform Length (WL) for the signal. Random Forest classification algorithm is implemented to classify the hand gestures achieved approximately 80% accuracy. The classified hand gestures for open and close hand were tested out on a prosthetic finger using Arduino Uno microcontroller to control the motor. The feature extraction, training, classification and serial communication which the Arduino microcontroller was all performed on MATLAB. The model is being trained more using more dataset to increase the accuracy for better performance.