04593nam 22007335 450 991029983630332120200629163439.03-319-16417-110.1007/978-3-319-16417-5(CKB)3710000000434066(EBL)2094526(SSID)ssj0001525117(PQKBManifestationID)11816143(PQKBTitleCode)TC0001525117(PQKBWorkID)11486099(PQKB)10958508(DE-He213)978-3-319-16417-5(MiAaPQ)EBC2094526(PPN)186395337(EXLCZ)99371000000043406620150610d2015 u| 0engur|n|---|||||txtccrState Estimation and Control for Low-cost Unmanned Aerial Vehicles[electronic resource] /by Chingiz Hajiyev, Halil Ersin Soken, Sıtkı Yenal Vural1st ed. 2015.Cham :Springer International Publishing :Imprint: Springer,2015.1 online resource (239 p.)Description based upon print version of record.3-319-16416-3 Includes bibliographical references and index.Introduction to Unmanned Aerial Vehicles -- Equations of Motion for the UAV -- Navigation Systems for UAV -- Estimation of the UAV Dynamics -- Estimation of the UAV Dynamics -- Estimation of the UAV Dynamics in the Presence of Sensor Faults -- Estimation of the UAV Dynamics in the Presence of Sensor/Actuator Faults -- Fault Detection, Isolation and Data Fusion for the UAV Air Data System -- Stability Analysis for the UAV -- Classical Controller Design for the UAV -- LQR Controller Design -- Fuzzy Logic Based Controller Design.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.Aerospace engineeringAstronauticsControl engineeringSignal processingImage processingSpeech processing systemsAerospace Technology and Astronauticshttps://scigraph.springernature.com/ontologies/product-market-codes/T17050Control and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Signal, Image and Speech Processinghttps://scigraph.springernature.com/ontologies/product-market-codes/T24051Aerospace engineering.Astronautics.Control engineering.Signal processing.Image processing.Speech processing systems.Aerospace Technology and Astronautics.Control and Systems Theory.Signal, Image and Speech Processing.620621.382629.1629.8Hajiyev Chingizauthttp://id.loc.gov/vocabulary/relators/aut721031Ersin Soken Halilauthttp://id.loc.gov/vocabulary/relators/autYenal Vural Sıtkıauthttp://id.loc.gov/vocabulary/relators/autBOOK9910299836303321State Estimation and Control for Low-cost Unmanned Aerial Vehicles2542728UNINA