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Real-time propojení senzorů pro navigaci
Kaczmarek, Adrian ; Rohm, Witold ; Klingbeil, Lasse ; Tchórzewski, Janusz
The development of satellite techniques in the field of precise positioning and the availability of mobile devices with a built-in multi-GNSS (Global Navigation Satellite System) receiver allow us to determine positions with better accuracy than a dozen or so years ago. At the same time, there is a growing demand from users for more and more accurate positioning while reducing the costs of the final device (e.g., a navigation system for autonomous lawn mowers). This work presents the concept of a solution that integrates different positioning techniques: gyroscopes, odometers, and GNSS using a loosely coupled Kalman filter. The sensor integration model was developed for horizontal components (2D) with simultaneous determination of azimuth and precise position. Additionally, the integration filter uses a dynamic weight matrix, the values of which are selected depending on the type of GNSS solution (FIX, FLOAT, etc.). Tests of the measurement platform were carried out under ideal conditions and in places where the horizon is obscured (passes along a high wall, under openwork steel trusses, etc.). The accuracies obtained during tests using EKF and the dynamic weight matrix are RMS 0.019 m for the North and East components. However, the accuracy of the azimuth determination was 0.59°. In addition, the presentation will present a platform concept that integrates low-cost sensors in real time.
This work was supported by Wroclaw University of Environmental and Life Sciences (Poland) under the project “POMOST” (grant no. N110/0002/22).
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Data processing in real-time fMRI neurofeedback
Bečička, Martin ; Slavíček, Tomáš (referee) ; Lamoš, Martin (advisor)
Tato práce se zabývá digitálním filtrováním dat získaných z fMRI neurofeedbacku v reálném čase. Práce analyzuje dosavadní řešení používané v CEITEC MU, se zaměřením na zkrácení prodlení na začátku každého neurofeedback bloku, které je způsobeno digitálním filtrováním. Dosavadní řešení používá, hlavně pro jeho online a vyhlazovací vlastnosti, nelineární Kalmánův filtr. Analýzou 150 průběhu fMRI neurofeedback sezení byla zjištěna dolní hranice, kterou nelineární Kalmánův filtr potřebuje k naučení. Počet potřebných vzorků je významně menši než je nastaveno v dosavadním řešení. Další možnosti zkrácení prodlení byly prozkoumány a klouzavý průměrovací filtr byl vybrán jako optimální kompromis mezi dobou prodlení, zpoždění filtru a jeho vyhlazovacími vlastnostmi.
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Permanent Magnet Synchronous Machine Sensorless Control Algorithms
Veselý, Libor ; Prokop, Roman (referee) ; Melichar,, Jiří (referee) ; Václavek, Pavel (advisor)
Algorithms of sensorless control of surface permanent magnet synchronous motors are discussed in the dissertation thesis. A method for position and speed estimation in high-speed region based on model reference adaptive system is described. Furthermore, classical approach using Kalman filtering was verified. Kalman filter expected the rotor speed to be constant as a modification of model using variable speed approach. These algorithms are not able to work at low speed region, thus a new method was proposed. This method is designed on extended Kalman filtering and uses the model which describes the stator inductance changes in - coordinates. At motor start, knowledge of initial rotor setup is required. The algorithm for initial rotor angle using high frequencies injected into the motor was proposed.
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Development of algorithms state estimation of experimental vehicle
Lamberský, Vojtěch ; Krejsa, Jiří (referee) ; Grepl, Robert (advisor)
This thesis deals with the filter algorithm design, implementing mathematical model to improve algorithm performance. Designed algorithms are implemented in a control unit of the experimental vehicle (filters signal used in the closed-loop controller). The improvement of the position estimation using Kalman Filter is demonstrated on the experimental vehicle. In the next part the design process of algorithm developing for dsPIC microcontroller using Matlab is described.
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The Appliances Immunity to Short Voltage Dips and Interruptions
Bok, Jaromír ; Beláň, Anton (referee) ; Santarius, Pavel (referee) ; Drápela, Jiří (advisor)
This Ph.D. thesis deals with problems about voltage dips and short voltage interruptions, generally named as voltage events, which origin in power supply networks and have a negative influence for all connected electric appliances. In this thesis single phase appliances are considered. These problems closely relate with area of electromagnetic compatibility which solve all questions about correct operation of different types of electric appliances during electromagnetic disturbances impact. Voltage events are ones of the many types of electromagnetic disturbances. The connection between disturbance sources and sensitive electric appliances is created by power supply lines. The immunity of electric appliances to voltage dips and short interruptions is currently tested via voltage dips with strictly defined parameters which are intended by class of electromagnetic environment in which the usage of electric appliance is recommended. During immunity tests the rectangular shape of voltage dips is preferred. The main descriptive parameters of testing voltage events are the residual voltage and the event time duration. But voltage dips and short interruptions defined by this way do not closely relate with parameters of real voltage dips and interruptions occurred in public supply system where parameters of voltage dips are variable. Moreover in the power supply system there are many of others voltage parameters which can have a significant influence to immunity level of connected electric appliances. This Ph.D. thesis also deals with finding more voltage event parameters. Although the voltage events occurrence in the power supply system is not limited and voltage events are considered only as informative voltage parameter it is important to monitor voltage events occurrence. The monitoring device has to be able to operate for ling time period and it has to detect parameters of voltage events with adequate accuracy. The accuracy of detected event parameters and the detection delay depends on the detection algorithm characteristics. That is why the part of this thesis relates with a comparison of several detection algorithms and their abilities to correct detection of voltage event parameters. The main purpose of this thesis is the proposal of connection between classification of voltage dips and short interruptions occurred in power supply system with the classification of electric appliances immunity to these voltage events. On the base of many of provided electric appliances immunity tests and also on the base of long time period voltage events monitoring the special compatibility levels are proposed in this thesis. The observation of proposed compatibility levels will bring the increasing level of reliable operation of all connected electric appliances.
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Navigation algorithm for INS/GPS Data Fusion
Pálenská, Markéta ; Ing.Petr Bojda,Ph.D. (referee) ; Čižmár, Jan (advisor)
Diplomová práce se zabývá návrhem algoritmu rozšířeného Kalmanova filtru, který integruje data z inerciálního navigačního systému (INS) a globálního polohovacího systému (GPS). Součástí algoritmu je i samotná mechanizace INS, určující na základě dat z akcelerometrů a gyroskopů údaje o rychlosti, zeměpisné pozici a polohových úhlech letadla. Vzhledem k rychlému nárůstu chybovosti INS je výstup korigován hodnotami rychlosti a pozice získané z GPS. Výsledný algoritmus je implementován v prostředí Simulink. Součástí práce je odvození jednotlivých stavových matic rozšířeného Kalmanova filtru.
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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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Measurement unit for sports analysis with inertial sensors
Dugas, Martin ; Brablc, Martin (referee) ; Kumpán, Pavel (advisor)
Master's thesis is dealing with desgin of a measuring unit incorporating inertial sensors, used for analysis in canoe sprint. Data from a three-axis accelerometer and a three-axis gyroscope were combined using an extended Kalman filter, yielding speed, roll, pitch and yaw of the boat and stroke rate. Calculated values were verified by a GPS. Furthermore, parameters describing dynamic behaviour of the system were identified, allowing an inclusion of dynamic quantities like force and power into the analysis.
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