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This paper is concerned with the development of methods for the validation of complex non-linear models of helicopter dynamics using measured flight data. The approach which has been adopted is based on the use of a series of simplified descriptions involving linearised models for each flight condition. Estimates of parameters in each of these linearised models, as found from the application of system identification techniques to flight data, are compared with parameter values in an equivalent linearised description obtained from the theoretical nonlinear model. In broad terms the aim is to achieve matching trends for both sets of parameters and thus establish the validity of the nonlinear model from which the linearised descriptions are derived. This use of system identification techniques as a means of validating flight mechanics models has required the development of improved tools for helicopter parameter identification. Frequency-domain methods of identification have been found to have advantages over more conventional time-domain methods. Important advantages of the methodology include the use of a restricted frequency range for the estimation of parameters of the rigid-body model and the incorporation of time delays into the model. Both of these are facilitated by the formulation of the problem in the frequency domain and have been found to provide practical benefits in the estimation of parameters of six-degrees-of-freedom models in which higher-order dynamics associated with rotor modes cannot be represented explicitly.
|Keywords:||Identification, helicopter, frequency-domain, flight mechanics model, validation|
|Glasgow Author(s) Enlighten ID:||Murray-Smith, Professor David|
|Authors:||Black, C.G., and Murray-Smith, D.J.|
|Subjects:||T Technology > TJ Mechanical engineering and machinery|
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics
|College/School:||College of Science and Engineering > School of Engineering > Systems Power and Energy|