dc.creator | Heredia Benot, Guillermo | es |
dc.creator | Ollero Baturone, Aníbal | es |
dc.date.accessioned | 2017-04-03T13:44:33Z | |
dc.date.available | 2017-04-03T13:44:33Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Heredia Benot, G. y Ollero Baturone, A. (2011). Detection of sensor faults in small helicopter UAVs using observer/Kalman filter identification. Mathematical Problems in Engineering, 2011 | |
dc.identifier.issn | 1024-123X | es |
dc.identifier.uri | http://hdl.handle.net/11441/56975 | |
dc.description.abstract | Reliability is a critical issue in navigation of unmanned aerial vehicles UAVs since there is no
human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant
sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be
installed in small UAVs. Therefore, other approaches like analytical redundancy should be used
to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault
detection and diagnosis system for small autonomous helicopters based on analytical redundancy.
Fault detection is accomplished by evaluating any significant change in the behaviour of the
vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The
observer is obtained from input-output experimental data with the Observer/Kalman Filter
Identification OKID method. The OKID method is able to identify the system and an observer
with properties similar to a Kalman filter, directly from input-output experimental data. Results
are similar to the Kalman filter, but, with the proposedmethod, there is no need to estimate neither
system matrices nor sensor and process noise covariance matrices. The system has been tested with
real helicopter flight data, and the results compared with other methods. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Hindawi Publishing Corporation | es |
dc.relation.ispartof | Mathematical Problems in Engineering, 2011 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | UAV's | es |
dc.subject | Detection | es |
dc.subject | Sensor | es |
dc.title | Detection of sensor faults in small helicopter UAVs using observer/Kalman filter identification | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.publisherversion | https://www.hindawi.com/journals/mpe/2011/174618/ | es |
dc.contributor.sponsorship | European Commission, ICT 2011-288082an | |
dc.contributor.sponsorship | Junta de Andalucía P09-TEP-5120. | |
dc.identifier.doi | 10.1155/2011/174618 | |
dc.contributor.group | Universidad de Sevilla. TEP151: Robotica, Vision y Control | es |
idus.format.extent | 21 p. | es |
dc.journaltitle | Mathematical Problems in Engineering | es |
dc.publication.volumen | 2011 | es |
dc.contributor.funder | European Commission (EC) | |
dc.contributor.funder | Junta de Andalucía | |