Hexarotor Yaw Flight Control with SPSA, PID Algorithm and Morphing

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Özet

In recent years, the interest in unmanned aerial vehicles (UAV) has increased. They have penetrated into all areas of life. However, studies on UAV control have been a frequently discussed topic by researchers. In this study, a hexarotor in which yaw flight is tried to be controlled by changing the arm lengths during flight (morphing) is discussed. The hexarotor mathematical model is linearly derived using Newton's equations of motion. The equations of motion are modeled using the state space model approach. Hexarotor has been drawn in Solidworks program in accordance with the reality of all morphing states. Morphing estimation and accordingly proportional-integral-derivative (PID) coefficients were estimated using Simultaneous Perturbation Stochastic Approximation (SPSA). SPSA was preferred because it converged to the optimum result faster than similar algorithms. Hexarotor simulations were performed in Matlab/Simulink environment. Hexarotor yaw flight stability was achieved by minimizing the SPSA generated cost function based on design performance criteria. The cost function converged in 3-4 iterations and approached the optimum result. Accordingly, the design performance criteria have also improved and successfully followed the given trajectory.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/13226Resmi atıflarda kullanılan kalıcı adres
Tam Kayıt
AlanDeğerDil
dc.contributor.authorKose, Oguz
dc.contributor.authorOktay, Tugrul
dc.date.accessioned2026-10-22T10:21:05.085586403Z
dc.date.available2026-10-22T10:21:05.085586403Z
dc.date.issued2022
dc.description.abstractIn recent years, the interest in unmanned aerial vehicles (UAV) has increased. They have penetrated into all areas of life. However, studies on UAV control have been a frequently discussed topic by researchers. In this study, a hexarotor in which yaw flight is tried to be controlled by changing the arm lengths during flight (morphing) is discussed. The hexarotor mathematical model is linearly derived using Newton's equations of motion. The equations of motion are modeled using the state space model approach. Hexarotor has been drawn in Solidworks program in accordance with the reality of all morphing states. Morphing estimation and accordingly proportional-integral-derivative (PID) coefficients were estimated using Simultaneous Perturbation Stochastic Approximation (SPSA). SPSA was preferred because it converged to the optimum result faster than similar algorithms. Hexarotor simulations were performed in Matlab/Simulink environment. Hexarotor yaw flight stability was achieved by minimizing the SPSA generated cost function based on design performance criteria. The cost function converged in 3-4 iterations and approached the optimum result. Accordingly, the design performance criteria have also improved and successfully followed the given trajectory.
dc.identifier.endpage221
dc.identifier.issn2147-6799
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85131782647
dc.identifier.startpage216
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/13226
dc.identifier.volume10
dc.language.isoen
dc.publisherIsmail Saritas
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectControl
dc.subjectHexarotor
dc.subjectMatlab
dc.subjectMorphing
dc.subjectNewton
dc.subjectPID
dc.subjectSolidworks
dc.subjectSPSA
dc.subjectUAV
dc.titleHexarotor Yaw Flight Control with SPSA, PID Algorithm and Morphing
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus24
rdl.oa.statusclosed
rdl.source.indexSCOPUS