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Control algorithms for BLDC motor for low speeds
Kozáček, Peter ; Pohl, Lukáš (referee) ; Veselý, Libor (advisor)
The diploma work concerns on an issue of data collection of speed and electrical angle based on informations from Hall sensor with the necessary resolution for control of BLDC motor. Specifically, concenred on a section with low speed. Most of moors use Hall sensor for detecting speed and position of the rotor. At low speed section, becomes the situation when we can not determine the position of the rotor with (the) required (sufficient) resolution, this situation creates a „wince“ in the control (ripple torque). The task is to design and evaluate the possibilities of the algorithm for control and acquisition speed and rotor position with the required accuracy.
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Postprocessing of GPS Logs
Jaška, Roman ; Pavelková, Alena (referee) ; Polok, Lukáš (advisor)
This thesis aims to analyse common errors in recorded GPS activities, identify algorithms suitable for correction of these problems and design and subsequently implement an Android application. The first chapter contains an introduction to the problem, demonstration of a few affected examples and explains the motivation behind the choice of this subject for my thesis. Second chapter decomposes the established problem. I specifically elaborate on the source of the errors, the format of input data, existing solutions, mathematical methods suitable for this problem, available APIs and reasons behind the selection of the final platform. Chapter number three describes the actual solution of the problem employed in the final application. The requirements for the final application are laid out as well as the specific details of the functionality, such as the usage of Kalman filter, individual APIs, libraries as well as the design of the user interface. The penultimate chapter reveals selected parts of the implementation, such as the Kalman filtering itself or the problem of manual track correction. This chapter also contains description of design changes executed during the implementation. The final chapter reviews the achieved results of Kalman filtering and snapping of points to roads using Google Maps Roads API. Ultimately, I elaborate on possibilities of continued development of the application.
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Browse the Map on Your Mobile Device by Moving the Device
Andraško, Daniel ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
This work deals with the creation of a mobile application that allows its user to view the map and move around it, without touching the screen, just by moving the device. The theoretical part of the thesis describes in more detail the inertial measurement unit and visual odometry , which can be used to determine the movement of the device. Next, a Kalman filter is described, which is used to refine the measured values of the accelerometer sensor. This sensor is part of an inertial measuring unit. The practical part of thesis describes the design of the mobile application and the implementation of the design. The end of thesis contains a description and evaluation of testing the final application on real users.
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Inertial Navigation Unit
Kulka, Branislav ; Kříž, Vlastimil (referee) ; Šolc, František (advisor)
This thesis is concerned with attitude estimation of small flying robots using low cost, small-sized inertial and magnetic sensors. A quaternion-based extended Kalman filter is used, which adaptively compensates external acceleration. External acceleration is the main source of estimation error. If external acceleration is detected, the accelerometer measurement covariance matrix of the Kalman filter is adjusted. The proposed algorithms are verified through experiments. Selected algorithm is implemented on STM32F4DISCOVERY development board.
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Vehicle speed estimation
Roštek, Martin ; Kumpán, Pavel (referee) ; Krejsa, Jiří (advisor)
Rýchlosť vozidla je jednou z kľúčových stavových premenných, ktorej znalosť je potrebná v reálnom čase a s vysokou presnosťou, aby mohla slúžiť ako vstupná veličina pre systémy kontroly dynamiky vozidla. Jej priame meranie vo vozidle je však finančne náročné. Riešením tohoto problému môže byť použitie meraní zo senzorov bežne dostupných na palube vozidla a ich následný prepočet na rýchlosť vozidla. Tieto merania sú však veľmi zaťažené procesným šumom, čo vyplýva z komplexnosti pohybu vozidla. Preto je nutné vyvinúť algoritmus so schopnosťou vysporiadať sa s týmito negatívnymi vplyvmi. Algoritmus prezentovaný v tejto práci odhaduje pozdĺžnu rýchlosť vozidla s použitím meraní uhlových rýchlostí štyroch kolies, pozdĺžnej akcelerácie, momentov motora, rýchlosti otáčania okolo zvislej osi a natočenia volantu. Algoritmus bol testovaný na veľkom počte situácií považovaných za kritické na odhad rýchlosti vozidla, ako napríklad prudká akcelerácia na vozovke s nízkym koeficientom trenia, núdzové brzdenie s aktiváciou ABS, či jazda v kopci s kolesami v preklze, prinášajúc uspokojujúce výsledky.
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Estimating of motion models and its parameters to identify target trajectory
Benko, Matej ; Eliaš, Michal (referee) ; Žák, Libor (advisor)
Táto práca sa zaoberá odstraňovaním šumu, ktorý vzniká z tzv. multilateračných meraní leteckých cieľov. Na tento účel bude využitá najmä teória Bayesovských odhadov. Odvodí sa aposteriórna hustota skutočnej (presnej) polohy lietadla. Spolu s polohou (alebo aj rýchlosťou) lietadla bude odhadovaná tiež geometria trajektórie lietadla, ktorú lietadlo v aktuálnom čase sleduje a tzv. procesný šum, ktorý charakterizuje ako moc sa skutočná trajektória môže od tejto líšiť. Odhad spomínaného procesného šumu je najdôležitejšou časťou tejto práce. Je odvodený prístup maximálnej vierohodnosti a Bayesovský prístup a ďalšie rôzne vylepšenia a úpravy týchto prístupov. Tie zlepšujú odhad pri napr. zmene manévru cieľa alebo riešia problém počiatočnej nepresnosti odhadu maximálnej vierohodnosti. Na záver je ukázaná možnosť kombinácie prístupov, t.j. odhad spolu aj geometrie aj procesného šumu.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Uhlíř, Václav (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors, provide sensor fusion and estimate position of robot based on this fusion. For solving I used knowledge about probabilistic robotics, robotic operating system, information fusion, filtering especially extended Kalman filter and robot localization. I created an application of extended Kalman filter as a result. Filter listen to messages from robot sensors, providing a sensor fusion and estimating position of the robot in environment. Filter can receive measurements from multiple sources. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Žák, Marek (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors and fuse them together. Afterwards use this data fusion of chosen sensors to estimate location of a robot. As a solution for these problems I have used my knowledge of Kalman filters, especially extended one. If messages from sensor measurements are well formulated, Kalman filter can perform fusion of measurements together with estimating the actual position of a robot. Filter can receive measurements from multiple sources and even from duplicities. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Design of a System for Precise Localization Services
Krippel, Martin ; Ščuglík, František (referee) ; Veselý, Vladimír (advisor)
The aim of this term project was to analyze wireless indoor localization. It contains analysis of some wireless localization techniques such as Time of Arrival or Time Difference of Arrival. The paper also describes the system of SEWIO Company. Main part of the master’s thesis is description, design and implementation of the Kalman filter. The Kalman filter is used to improve two-dimensional positional data and synchronization of anchors (devices for finding a position of an object in SEWIO system). There are described a few system models for the Kalman filter.
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Radar Sensor for Active Cruise Control
Lacek, Richard ; Zemčík, Pavel (referee) ; Maršík, Lukáš (advisor)
The aim of the work was to design the implementation of adaptive cruise control with the help of radar as a sensor to evaluate the surroundings in front of the vehicle. The solution used the VCDS-Lite application to determine the current vehicle speed and the Medium Range Radar demo, from Texas Instruments, to capture the surroundings in front of the vehicle with AWR1843 radar. Using these two applications was evaluated the environment in front of the vehicle from which the instruction for a driver was derived. The result of the work is an application that displays the current vehicle speed along with the current adaptive cruise control instruction. In addition to setting the speed, the application also provides a setting of the time interval from the vehicle that follows.
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