Parameterised analytical models that describe the trimmed inflight behaviour of classical
aircraft have been studied and are widely accepted by the flight dynamics community.
Therefore, the primary role of aircraft parameter estimation is to quantify the parameter
values which make up the models and define the physical relationship of the air vehicle with
respect to its local environment. Nevertheless, a priori empirical predictions dependent
on aircraft design parameters also exist, and these provide a useful means of generating
preliminary values predicting the aircraft behaviour at the design stage. However, at
present the only feasible means that exist to actually prove and validate these parameter
values remains to extract them through physical experimentation either in a wind-tunnel
or from a flight test. With the advancement of UAVs, and in particular smaller UAVs
(less than 1m span) the ability to fly the full scale vehicle and generate flight test data
presents an exciting opportunity. Furthermore, UAV testing lends itself well to the ability
to perform rapid prototyping with the use of COTS equipment.
Real-time system identification was first used to monitor highly unstable aircraft behaviour
in non-linear flight regimes, while expanding the operational flight envelope. Recent
development has focused on creating self-healing control systems, such as adaptive
re-configurable control laws to provide robustness against airframe damage, control surface
failures or inflight icing. In the case of UAVs real-time identification, would facilitate rapid
prototyping especially in low-cost projects with their constrained development time. In
a small UAV scenario, flight trials could potentialy be focused towards dynamic model
validation, with the prior verification step done using the simulation environment. Furthermore,
the ability to check the estimated derivatives while the aircraft is flying would
enable detection of poor data readings due to deficient excitation manoeuvres or atmospheric
turbulence. Subsequently, appropriate action could then be taken while all the
equipment and personnel are in place.
This thesis describes the development of algorithms in order to perform online system
identification for UAVs which require minimal analyst intervention. Issues pertinent
to UAV applications were: the type of excitation manoeuvers needed and the necessary
instrumentation required to record air-data. Throughout the research, algorithm development
was undertaken using an in-house Simulink© model of the Aerosonde UAV which
provided a rapid and flexible means of generating simulated data for analysis. In addition,
the algorithms were further tested with real flight test data that was acquired from
the Cranfield University Jestream-31 aircraft G-NFLA during its routine operation as a
flying classroom. Two estimation methods were principally considered, the maximum likelihood
and least squares estimators, with the aforementioned found to be best suited to
the proposed requirements. In time-domain analysis reconstruction of the velocity state
derivatives ˙W and ˙V needed for the SPPO and DR modes respectively, provided more statistically
reliable parameter estimates without the need of a α- or β- vane. By formulating
the least squares method in the frequency domain, data issues regarding the removal of
bias and trim offsets could be more easily addressed while obtaining timely and reliable
parameter estimates. Finally, the importance of using an appropriate input to excite the
UAV dynamics allowing the vehicle to show its characteristics must be stressed.
| Identifer | oai:union.ndltd.org:CRANFIELD1/oai:dspace.lib.cranfield.ac.uk:1826/8058 |
| Date | 07 1900 |
| Creators | Jameson, Pierre-Daniel |
| Contributors | Cooke, A. K. |
| Publisher | Cranfield University |
| Source Sets | CRANFIELD1 |
| Language | English |
| Detected Language | English |
| Type | Thesis or dissertation, Doctoral, PhD |
| Rights | © Cranfield University 2013. All rights reserved. No part of this publication may be reproduced without the permission of the copyright holder |
Page generated in 0.0028 seconds