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dc.contributor.advisorSteck, James E.
dc.contributor.authorSubba Reddiar Pappu, Venkatasubramani
dc.date.accessioned2015-03-02T21:44:43Z
dc.date.available2015-03-02T21:44:43Z
dc.date.issued2014-07
dc.identifier.othert14057
dc.identifier.urihttp://hdl.handle.net/10057/11127
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Aerospace Engineering
dc.description.abstractThe aim of this research is to assess the capability of Modified State Observer (MSO) based adaptations for use in controlling the longitudinal flight dynamics of a General Aviation (GA) type airplane and a Micro Aerial Vehicle (MAV). For the GA type aircraft, the report details the issues encountered while flight testing a neural network based Model Reference Adaptive Controller (MRAC), on a General Aviation fly-by-wire test bed. The flight test results of the MRAC presented in this report show PLA surging issues due to adaptation during the commanded flight path angle and airspeed. To overcome this problem, MSO based adaptation methodology is adopted to control the longitudinal dynamics of a typical general aviation aircraft. The advantage of MSO is that it adapts to estimation error, not modeling or tracking error. A controlled flight simulation is carried out including the turbulence effects observed during flight. The simulation results show the controller is able to track flight path angle and airspeed commands in the presence of turbulence. The random PLA surge seen during the simulation and flight test of the baseline MRAC controller is not observed in the simulation results of MSO adaptation controller. For the MAV, the simulation is carried out using the aerodynamic derivatives of the Black Kite 300 mm wing span MAV developed by CSIR-NAL Bangalore. The controller is tested in simulation for its ability to adapt to modeling errors for the highly responsive MAV. Simulation results are presented that show the MSO based adaptive controller's ability to respond to altitude and airspeed commands with elevator and engine failures in the presence of parameter uncertainties. The MSO adaptation, along with the nonlinear dynamic inverse controller developed using the mathematical model of the MAV, enables the pilot to control the vehicle with a lower workload.
dc.format.extentxv, 74 p.
dc.language.isoen_US
dc.publisherWichita State University
dc.rightsCopyright 2014 Venkatasubramani Subba Reddiar Pappu
dc.subject.lcshElectronic dissertations
dc.titleModified state observer based adaptive control law for general aviation and micro aerial vehicles
dc.typeThesis


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  • AE Theses and Dissertations
    Electronic copies of theses and dissertations defended in the Department of Aerospace Engineering
  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • Master's Theses
    This collection includes Master's theses completed at the Wichita State University Graduate School (Fall 2005 --)

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