State Estimation and Control for Low-cost Unmanned Aerial Vehicles

Nonfiction, Science & Nature, Technology, Automation, Aeronautics & Astronautics
Cover of the book State Estimation and Control for Low-cost Unmanned Aerial Vehicles by Chingiz Hajiyev, Halil Ersin Soken, Sıtkı Yenal Vural, Springer International Publishing
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Author: Chingiz Hajiyev, Halil Ersin Soken, Sıtkı Yenal Vural ISBN: 9783319164175
Publisher: Springer International Publishing Publication: June 10, 2015
Imprint: Springer Language: English
Author: Chingiz Hajiyev, Halil Ersin Soken, Sıtkı Yenal Vural
ISBN: 9783319164175
Publisher: Springer International Publishing
Publication: June 10, 2015
Imprint: Springer
Language: English

This book discusses state estimation and control procedures for a low-cost unmanned aerial vehicle (UAV). The authors consider the use of robust adaptive Kalman filter algorithms and demonstrate their advantages over the optimal Kalman filter in the context of the difficult and varied environments in which UAVs may be employed. Fault detection and isolation (FDI) and data fusion for UAV air-data systems are also investigated, and control algorithms, including the classical, optimal, and fuzzy controllers, are given for the UAV. The performance of different control methods is investigated and the results compared.

State Estimation and Control of Low-Cost Unmanned Aerial Vehicles covers all the important issues for designing a guidance, navigation and control (GNC) system of a low-cost UAV. It proposes significant new approaches that can be exploited by GNC system designers in the future and also reviews the current literature. The state estimation, control and FDI methods are illustrated by examples and MATLAB® simulations.

State Estimation and Control of Low-Cost Unmanned Aerial Vehicles will be of interest to  both  researchers  in  academia  and  professional  engineers  in  the aerospace  industry. Graduate students may also find it useful, and some sections are suitable for an undergraduate readership.

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This book discusses state estimation and control procedures for a low-cost unmanned aerial vehicle (UAV). The authors consider the use of robust adaptive Kalman filter algorithms and demonstrate their advantages over the optimal Kalman filter in the context of the difficult and varied environments in which UAVs may be employed. Fault detection and isolation (FDI) and data fusion for UAV air-data systems are also investigated, and control algorithms, including the classical, optimal, and fuzzy controllers, are given for the UAV. The performance of different control methods is investigated and the results compared.

State Estimation and Control of Low-Cost Unmanned Aerial Vehicles covers all the important issues for designing a guidance, navigation and control (GNC) system of a low-cost UAV. It proposes significant new approaches that can be exploited by GNC system designers in the future and also reviews the current literature. The state estimation, control and FDI methods are illustrated by examples and MATLAB® simulations.

State Estimation and Control of Low-Cost Unmanned Aerial Vehicles will be of interest to  both  researchers  in  academia  and  professional  engineers  in  the aerospace  industry. Graduate students may also find it useful, and some sections are suitable for an undergraduate readership.

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