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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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Comparison Of Different Approaches To
Adaptation Of Unscented Kalman Filter
For Non-Odometry Slam
Klečka, Jan
This paper is aimed at utilizing of an Unscented Kalman filter (UKF) for application on non-odometry SLAM problem. Non-odometry SLAM problem lacks state transitions function for part of state vector so theoretical part of the paper describes the derivation of three proposed modifications. The experimental part then shows experiments which evaluate modifications performance in reference to Extended Kalman filter. Experiments are based on simulation of monocular photogrammetry reconstruction problem.
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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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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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