MARC details
| 000 -LEADER |
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| fixed length control field |
04013ntm a2200373 i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000105296 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251117113402.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
180925t20182018my a f a m 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0008060(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
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| Level of rules in bibliographic description |
201906190843 |
| Level of effort used to assign nonsubject heading access points |
amy2 |
| -- |
201809251523 |
| -- |
fateeha |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMP |
| Language of cataloging |
eng |
| Transcribing agency |
UMP |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FKEE .C43 2018 r Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Chan, Shi Jing, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
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| Title |
Hybrid fault detection using kalman filter and neural network for quadrotor micro aerial vehicle / |
| Statement of responsibility, etc. |
Chan Shi Jing |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMP, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2018 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
© 2018 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiii, 110 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Source |
rdacontent |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Media type term |
unmediated |
| Source |
rdamedia |
| 337 ## - MEDIA TYPE |
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| Media type term |
computer |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Carrier type term |
volume |
| Source |
rdacarrier |
| 338 ## - CARRIER TYPE |
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| Carrier type term |
computer disc |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
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| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 500 ## - GENERAL NOTE |
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| General note |
Faculty of Electrical and Electronics Engineering |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Master of Science) -- Universiti Malaysia Pahang – 2018 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
This thesis introduces the application of time-domain Hybrid Fault Detection (HFD) methods for application in a quadrotor Micro Aerial Vehicle (MAV). The application aims to solve one of the main problems of the quadrotor, which is its inability to reach the exact target location that the user intended. The problem may be due to a faulty signal happened in the sensor or the actuator side or both, causing the quadrotor unable to complete the task given. Among the reasons of the faulty signal are the occurrences of signal in quadrotor, in the sensor or actuator side, as well as possible communication problem. When actuator fault, sensor fault or both faults occur, the controllers cannot function well and hence its performance reduce. At the initial control design stage of quadrotor, it is usually designed under the assumption that no faults would occur in quadrotors. The Faulty Detection (FD) method is therefore crucial to ensure quadrotor system can work properly and efficiently. The proposed method for the fault detection in this study uses hybrid technique which combines the extended kalman filter and artificial neural network (ANN). Two classes of approaches are analysed: the fault system identification approach ANN and the observer-based approach using the extended kalman filter. The extended kalman filter recognizes data from the sensors of the system and indicates the residuals of the system in the sensor reading. Residuals prediction is based on the fault magnitude and the time occurrence of fault. The information will then be fed to ANN, which consists of a bank of parameter estimation that generates the failure state. ANN is an algorithm that is used to determine the fault condition and determine its severity in the quadrotor system. ANN is designed based on nonlinear autoregressive network with exogenous inputs (NARX) scheme so that it can be trained to generate output based on the simulation behaviours of the quadrotor. The different fault locations are used as input vectors for training an artificial neural network (ANN). The result of the residual signal before filtration and after filtration showed that Kalman-ANN is able to identify single fault as well as multiple faults. For all individual faults including the multiple fault detection, the accuracy of the detection is 78.89 percent. It can be conclude that the newly proposed hybrid FD method in this thesis is able to accurately detect the location fault, for both the sensor and actuator faults simultaneous in the quadrotor. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
Faculty of Electrical and Electronics Engineering |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Disertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Theses |