• Login
    View Item 
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • ETD: Electronic Theses and Dissertations
    • Master's Theses
    • View Item
    •   Shocker Open Access Repository Home
    • Graduate Student Research
    • ETD: Electronic Theses and Dissertations
    • Master's Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Adaptive critic flight control for a general aviation aircraft: Simulations for the beech bonanza fly-by-wire testbed

    View/Open
    Thesis (491.2Kb)
    Date
    2007-07
    Author
    Chandramohan, Rajeev
    Advisor
    Steck, James E.
    Metadata
    Show full item record
    Abstract
    An adaptive and reconfigurable flight control system is developed for a general aviation aircraft. The flight control system consisting of two neural networks is developed using a two phase procedure called the pre-training phase and the online training phase. The adaptive critic method used in this thesis was developed by Ferrari and Stengel. In the pre-training phase the architecture and initial weights of the neural network are determined based on linear control. A set of local gains for the linearized model of the plant is obtained at different design points on the velocity v/s altitude envelope using an LQR method. The pre-training phase guarantees that the neural network controller meets the performance specifications of the linear controllers at the design points. Online training uses a dual heuristic adaptive critic architecture that trains the two networks to meet performance specifications in the presence of nonlinearities and control failures. The control system developed is implemented for a three-degree-of-freedom longitudinal aircraft simulation. As observed from the results the adaptive control system meets performance requirements, specified in terms of the damping ratio of the phugoid and short period modes, in the presence of nonlinearities. The neural network controller also compensates for partial elevator and thrust failures. It is also observed that the neural network controller meets the performance specification for large variations in the parameters of the assumed and actual models.
    Description
    Thesis (M.S)--Wichita State University, College of Engineering, Dept. of Aerospace Engineering

    "July 2007."
    URI
    http://hdl.handle.net/10057/1509
    Collections
    • AE Theses and Dissertations
    • CE Theses and Dissertations
    • Master's Theses

    Browse

    All of Shocker Open Access RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsBy TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace software copyright © 2002-2023  DuraSpace
    DSpace Express is a service operated by 
    Atmire NV