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Algorithms of Electrical Drives State Estimation
Herman, Ivo ; Vavřín, Petr (referee) ; Václavek, Pavel (advisor)
This thesis deals with state estimation methods for AC drives sensorless control and with possibilities of the estimation. Conditions for observability for a synchronous drive were derived, as well as conditions for the moment of inertia and the load torque observability for both drive types - synchronous and asynchronous. The possibilities of the estimation were confirmed by experimental results. The covariance matrices for all filters were found using an EM algorithm. Both drives were also identified. The algoritms used for state estimation are Extended Kalman Filter, Unscented Kalman Filter, Particle Filters and Moving Horizon Estimator.
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Camera Orientation in Real-Time
Župka, Jiří ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
This work deals with the orientation of the camera in real-time with a single camera. Offline methods are described and used as a reference for comparison of a real-time metods. Metods work in real-time Monocular SLAM and PTAM methods are there described and compared. Further, paper shows hints of advanced methods whereas future work is possible.
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Sensorless control of BLDC motor
Hrbáč, Zbyněk ; Grepl, Robert (referee) ; Sova, Václav (advisor)
This thesis is focused on the sensorless control of BLDC motor using the Extended Kalman filter. In the first section, process of EKF implementation for estimating rotor speed and electrical angle is described. For this estimation, EKF uses non-linear BLDC motor model and some measurement containing random noise. Second part deals with designing methodology to measure and estimate the quality of BLDC motor sensorless control. Best results were achieved with total current entering power electronics ripple analyzation. In the last section, several BLDC sensorless control algorithms were evaluated.
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HIGH POWER-EFFICIENT SENSORLESS CONTROL OF SYNCHRONOUS RELUCTANCE MOTOR
Mynář, Zbyněk ; Talla,, Jakub (referee) ; Lettl, Jiří (referee) ; Václavek, Pavel (advisor)
Synchronní reluktanční motory se pro svou relativně vysokou účinnost, robustnost a nízkou cenu stávají stále populárnější alternativou velmi rozšířených asynchronních motorů. Snaha o využití výhodných vlastností bezsnímačového řízení, a dosažení co nejvyšší účinnost jejich provozu, je však komplikována jejich výraznou nelinearitou způsobenou saturací magnetického obvodu. Úvod této práce je věnován popisu matematicko-fyzikálního modelu SynRM a přehledu existujících moderních algoritmů výkonově-optimálního bezsnímačového řízení. Jádrem práce je pak představení estimátoru stavů a parameterů SynRM postaveného na novém přístupu k měření a využití fázových reluktancí. Klíčovými prvky algoritmu jsou nová metodologie měření fázových reluktancí, spínací PWM schéma jež umožňuje snížit spínací ztráty a měřit fázové reluktance od nulových otáček, a nakonec integrace těchto měření s matematickým modelem SynRM s pomocí rozšířeného Kalmánova filtru. Experimentální část práce pak diskutuje výsledky reálných měření s navrženým algoritmem a vybranými současnými algoritmy.
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Autonomous driving concept for Formula Student
Pavel, Matěj ; Štětina, Josef (referee) ; Porteš, Petr (advisor)
The goal of the paper is to propose a new iteration of TU Brno Racing’s autonomous driving system. It first concerns itself with a general overview of autonomous vehicles and the rules of the Formula Student competition and an analysis of the current solution, with discussion of its flaws. Next, a solution is proposed to one of those flaws – vehicle localization utilizing an Extended Kalman Filter (EKF) for sensor fusion. Necessary filtering and transformations of the data are discussed. Finally, the paper contains a choice of sensors potentially useful for further increases in accuracy of the localization system.
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Camera Orientation in Real-Time
Župka, Jiří ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
This work deals with the orientation of the camera in real-time with a single camera. Offline methods are described and used as a reference for comparison of a real-time metods. Metods work in real-time Monocular SLAM and PTAM methods are there described and compared. Further, paper shows hints of advanced methods whereas future work is possible.
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Sensorless control of BLDC motor
Hrbáč, Zbyněk ; Grepl, Robert (referee) ; Sova, Václav (advisor)
This thesis is focused on the sensorless control of BLDC motor using the Extended Kalman filter. In the first section, process of EKF implementation for estimating rotor speed and electrical angle is described. For this estimation, EKF uses non-linear BLDC motor model and some measurement containing random noise. Second part deals with designing methodology to measure and estimate the quality of BLDC motor sensorless control. Best results were achieved with total current entering power electronics ripple analyzation. In the last section, several BLDC sensorless control algorithms were evaluated.
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Algorithms of Electrical Drives State Estimation
Herman, Ivo ; Vavřín, Petr (referee) ; Václavek, Pavel (advisor)
This thesis deals with state estimation methods for AC drives sensorless control and with possibilities of the estimation. Conditions for observability for a synchronous drive were derived, as well as conditions for the moment of inertia and the load torque observability for both drive types - synchronous and asynchronous. The possibilities of the estimation were confirmed by experimental results. The covariance matrices for all filters were found using an EM algorithm. Both drives were also identified. The algoritms used for state estimation are Extended Kalman Filter, Unscented Kalman Filter, Particle Filters and Moving Horizon Estimator.
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Sensorless Vector Control of Induction Motor
Kokeš, Petr
For sensorless IM control, the problem of simultaneous estimation of inner non-measurable IM state quantities and one or more slowly changing parameters must be solved. For this purpose, the Extended Kalman Filter (EKF) was chosen and an EKF of 7th order was designed to estimate magnetic flux linkage of the stator and rotor and also IM speed and stator and rotor resistances. The IM model was then extended to the 9th order and the corresponding 9th order EKF enabled to estimate further stator parameters. Theoretical solutions were verified by computer simulations and also by practical experiments with a 2,2kW IM fed from 4-level VSI.
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