Control Power Optimization using Artificial Intelligence for Forward Swept Wing and Hybrid Wing Body Aircraft

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dc.contributor.authorAdegbindin, Moustaine Kolawole Agnideen
dc.contributor.committeechairSchetz, Joseph A.en
dc.contributor.committeechairKapania, Rakesh K.en
dc.contributor.committeememberPatil, Mayuresh J.en
dc.contributor.departmentAerospace and Ocean Engineeringen
dc.date.accessioned2017-02-07T09:01:08Zen
dc.date.available2017-02-07T09:01:08Zen
dc.date.issued2017-02-06en
dc.description.abstractMany futuristic aircraft such as the Hybrid Wing Body have numerous control surfaces that can result in large hinge moments, high actuation power demands, and large actuator forces/moments. Also, there is no unique relationship between control inputs and the aircraft response. Distinct sets of control surface deflections may result in the same aircraft response, but with large differences in actuation power. An Artificial Neural Network and a Genetic Algorithm were used here for the control allocation optimization problem of a Hybrid Wing Body to minimize the Sum of Absolute Values of Hinge Moments for a 2.5-G pull-up maneuver. To test the versatility of the same optimization process for different aircraft configurations, the present work also investigates its application on the Forward Swept Wing aircraft. A method to improve the robustness of the process is also presented. Constraints on the load factor and longitudinal pitch rate were added to the optimization to preserve the trim constraints on the control deflections. Another method was developed using stability derivatives. This new method provided better results, and the computational time was reduced by two orders of magnitude. A hybrid scheme combining both methods was also developed to provide a real-time estimate of the optimum control deflection schedules to trim the airplane and minimize the actuation power for changing flight conditions (Mach number, altitude and load factor) in a pull-up maneuver. Finally, the stability derivatives method and the hybrid scheme were applied for an antisymmetric, steady roll maneuver.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:9611en
dc.identifier.urihttp://hdl.handle.net/10919/74950en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectOptimizationen
dc.subjectArtificial Intelligenceen
dc.subjectNeural Networken
dc.subjectGenetic Algorithmen
dc.subjectForward Swept Wingen
dc.subjectHybrid Wing Bodyen
dc.subjectHinge Momenten
dc.titleControl Power Optimization using Artificial Intelligence for Forward Swept Wing and Hybrid Wing Body Aircraften
dc.typeThesisen
thesis.degree.disciplineAerospace Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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