FRACTIONAL ORDER CHAOTIC MODEL BASED ENHANCED EQUILIBRIUM OPTIMIZATION ALGORITHM FOR CONTROLLER DESIGN OF 3 DOF HOVER FLIGHT SYSTEM

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dc.contributor.authorAtes, Abdullah
dc.contributor.authorChen, YangQuan
dc.date.accessioned2024-08-04T20:58:52Z
dc.date.available2024-08-04T20:58:52Z
dc.date.issued2021
dc.departmentİnönü Üniversitesien_US
dc.descriptionASME International Design Engineering Technical Conferences / 41st Annual Computers and Information in Engineering Conference (IDETC-CIE) / 17th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA) -- AUG 17-19, 2021 -- ELECTR NETWORKen_US
dc.description.abstractIn this study, the K feedback gain vector parameters that are used for the control of three degree of freedom four rotor quadcopter system (3 DOF Hover) are optimized with the Enhanced Equilibrium Optimization Algorithm ((EO)-O-2). The (EO)-O-2 algorithm is proposed with using parameters obtained from fractional order chaotic oscillator models instead of random variables. The Basic EO algorithm is inspired by volume- mass balance. In EO algorithm, each particle is called a motion that searches a parameter vector space. However, random coefficients derived from uniform distribution are used in the parameters updating process or in the generation of the initial population. The (EO)-O-2 algorithm was proposed by using vectors obtained from fractional order chaotic oscillators instead of stochastic coefficients in the basic Equilibrium optimization algorithm. Genesio Tesi, Rossler, Lotka Volterra fractional-order chaotic oscillator models were used in the (EO)-O-2 algorithm to optimize K feedback gain vector of 3 DOF Hover. The order and initial conditions the fractional chaotic oscillator models were experimentally adjusted for the control of 3 DOF problem. Thus, suitable fractional-order chaotic models for the problem were obtained. The (EO)-O-2 algorithm results are compared with the Stochastic Multi Parameter Optimization (SMDO) and Discreet Stochastic Optimization (DSO) algorithms for the system's pitch, roll and yaw angles.en_US
dc.description.sponsorshipAmer Soc Mech Engineers, Design Engn Div,Amer Soc Mech Engineers, Comp & Informat Engn Div, Tech Comm Micro & Nano Syst,IEEEen_US
dc.identifier.isbn978-0-7918-8543-7
dc.identifier.urihttps://hdl.handle.net/11616/103231
dc.identifier.wosWOS:001224362100018en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherAmer Soc Mechanical Engineersen_US
dc.relation.ispartofProceedings of Asme 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Idetc-Cie2021, Vol 7en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFractional Calculusen_US
dc.subjectSwarm intelligence optimization algorithmen_US
dc.subjectControlen_US
dc.titleFRACTIONAL ORDER CHAOTIC MODEL BASED ENHANCED EQUILIBRIUM OPTIMIZATION ALGORITHM FOR CONTROLLER DESIGN OF 3 DOF HOVER FLIGHT SYSTEMen_US
dc.typeConference Objecten_US

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