|
|
Modern Flight Control System Design and Evaluation
Vlk, Jan ; Holzapfel, Florian (oponent) ; Rzucidlo, Pawel (oponent) ; Mathan, Santosh (oponent) ; Chudý, Peter (vedoucí práce)
This thesis addresses the research on modern methods in automatic Flight Control System design and evaluation, as seen from the perspective of state-of-the-art and future utilization on Unmanned Aerial Systems. The thesis introduces a Flight Control System design process with a special emphasis on the Model-Based Design approach. An integral part of this process is the creation of the aircraft's mathematical model employed in the flight control laws synthesis and the composition of a simulation framework for the evaluation of the automatic Flight Control System's stability and performance. The core of this thesis is aimed at flight control laws synthesis built around a unique blend of optimal and adaptive control theory. The researched flight control laws originating from the proposed design process were integrated into an experimental digital Flight Control System. The final chapter of the thesis introduces the evaluation of the designed automatic Flight Control System and is divided into three phases. The first phase contains the Robustness Evaluation, which investigates the stability and robustness of the designed control system within the frequency domain. The second phase is the controller's Performance Evaluation employing computer simulations using created mathematical models in the time domain. As for the final phase, the designed Flight Control System is integrated into an experimental aircraft platform, serving as a testbed for future Unmanned Aerial Systems, and subjected to a series of flight tests.
|
|
|
Algoritmy odhadu stavových veličin elektrických pohonů
Herman, Ivo ; Vavřín, Petr (oponent) ; Václavek, Pavel (vedoucí práce)
Práce se zabývá metodami odhadu stavů pro střídavé motory a podmínkami odhadu těchto stavů. Odvozeny byly podmínky pozorovatelnosti pro synchronní motor a dále pro odhad momentu setrvačnosti a momentu zátěže pro oba typy motorů - synchronní i indukční. Možnosti odhadu byly potvrzeny i experimentálně na reálných datech. Kovarianční matice pro všechny filtry byly nalezeny pomocí EM algoritmu. Pro oba typy motorů byla též provedena identifikace. Pro odhad stavů byly použity estimátory Rozšířený Kalmanův filtr, Unscented Kalman Filter, Particle filters a estimátor s plovoucím horizontem (MHE)
|
|
|
Vehicle speed estimation
Roštek, Martin ; Kumpán, Pavel (oponent) ; Krejsa, Jiří (vedoucí práce)
Vehicle speed is one of the crucial variables needed to be known in real-time and with high accuracy, to serve as input into vehicle dynamic control systems. Its direct measurement in the vehicle is however cost ineffective. The idea is to use the measurements from generally available on-board sensors and to consequently compute the vehicle speed. Nevertheless, the measurements are highly influenced by process noises due to complexity of motion of the vehicle. Therefore, an estimation algorithm with ability to deal with this negative influence has to be developed. The estimation algorithm presented in this thesis estimates longitudinal vehicle speed using measurements of four rotational wheel speeds, longitudinal acceleration, motor torques, yaw rate and steering wheel angle. It was tested against the numerous situations considered critical according to vehicle speed estimation, such as rapid acceleration on road with low friction coefficient, emergency braking with activation of ABS, or driving in the slope with wheels slipping, providing satisfactory results.
|
|
|
Hybrid Method for Modelling and State Estimation of Dynamic Systems
Brablc, Martin ; Blaha, Petr (oponent) ; Bugeja, Marvin (oponent) ; Grepl, Robert (vedoucí práce)
This Doctoral thesis deals with the development of a new hybrid method for the dual estimation of states and parameters of nonlinear dynamic systems based on the idea of local linear models, which uses the estimation of the uncertainty of the model parameters to automatically adjust the parameters of the Kalman filter (KF), thus greatly simplifying its deployment and adjustment in practical applications. In the first part, the dissertation summarises the current state of knowledge in the field of dynamic systems, simultaneous estimation, KF and modelling of nonlinear dynamic systems. Then, in two separate chapters, it discusses the modification of KF for situations where inaccurate model parameters are the dominant influence causing process noise, and the modification of the Receptive field weighted regression (RFWR) method so that it can be used for dual estimation. Finally, the paper describes the developed hybrid method composed of modified RFWR and KF algorithms called Receptive field dual estimation - (RFDE) and demonstrates its performance on simulation and real data.
|
|
|
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
Vlk, T. ; Dedecius, Kamil
The state-of-the-art algorithms for Kalman filtering in agent networks with information diffusion impose the requirement of well-defined state-space models. In particular, they assume that both the process and measurement noise covariance matrices are known and properly set. This is a relatively strong assumption in the signal processing domain. By design, the Kalman filters are rather sensitive to its violation, which may potentially lead to their divergence. In this paper, we propose a novel distributed filtering algorithm with increased robustness under unknown process and measurement noise covariance matrices. It is formulated as a Bayesian variational message passing procedure for simultaneous analytically tractable inference of states and measurement noise covariance matrices.
|
|
|
Modern Flight Control System Design and Evaluation
Vlk, Jan ; Holzapfel, Florian (oponent) ; Rzucidlo, Pawel (oponent) ; Mathan, Santosh (oponent) ; Chudý, Peter (vedoucí práce)
This thesis addresses the research on modern methods in automatic Flight Control System design and evaluation, as seen from the perspective of state-of-the-art and future utilization on Unmanned Aerial Systems. The thesis introduces a Flight Control System design process with a special emphasis on the Model-Based Design approach. An integral part of this process is the creation of the aircraft's mathematical model employed in the flight control laws synthesis and the composition of a simulation framework for the evaluation of the automatic Flight Control System's stability and performance. The core of this thesis is aimed at flight control laws synthesis built around a unique blend of optimal and adaptive control theory. The researched flight control laws originating from the proposed design process were integrated into an experimental digital Flight Control System. The final chapter of the thesis introduces the evaluation of the designed automatic Flight Control System and is divided into three phases. The first phase contains the Robustness Evaluation, which investigates the stability and robustness of the designed control system within the frequency domain. The second phase is the controller's Performance Evaluation employing computer simulations using created mathematical models in the time domain. As for the final phase, the designed Flight Control System is integrated into an experimental aircraft platform, serving as a testbed for future Unmanned Aerial Systems, and subjected to a series of flight tests.
|
|
| |
|
|
Vehicle speed estimation
Roštek, Martin ; Kumpán, Pavel (oponent) ; Krejsa, Jiří (vedoucí práce)
Vehicle speed is one of the crucial variables needed to be known in real-time and with high accuracy, to serve as input into vehicle dynamic control systems. Its direct measurement in the vehicle is however cost ineffective. The idea is to use the measurements from generally available on-board sensors and to consequently compute the vehicle speed. Nevertheless, the measurements are highly influenced by process noises due to complexity of motion of the vehicle. Therefore, an estimation algorithm with ability to deal with this negative influence has to be developed. The estimation algorithm presented in this thesis estimates longitudinal vehicle speed using measurements of four rotational wheel speeds, longitudinal acceleration, motor torques, yaw rate and steering wheel angle. It was tested against the numerous situations considered critical according to vehicle speed estimation, such as rapid acceleration on road with low friction coefficient, emergency braking with activation of ABS, or driving in the slope with wheels slipping, providing satisfactory results.
|
|
| |
|
| |
host ::
RSS.