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Optimum design of a PID controller for the adaptive torsion wing

Published online by Cambridge University Press:  27 January 2016

M. Bourchak ,
R. M. Ajaj ,
E. I. Saavedra Flores ,
M. Khalid  and
K. A. Juhany
M. Bourchak
Affiliation:
Aeronautics and Astronautics, University of Southampton, Southampton, UK Aeronautical Engineering Department, King Abdulaziz UniversityJeddah, Saudi Arabia
R. M. Ajaj*
Affiliation:
Aeronautics and Astronautics, University of Southampton, Southampton, UK
E. I. Saavedra Flores
Affiliation:
Departamento de Ingeniería en Obras Civiles, Universidad de Santiago de Chile, Santiago, Chile
M. Khalid
Affiliation:
Aeronautical Engineering Department, King Abdulaziz UniversityJeddah, Saudi Arabia
K. A. Juhany
Affiliation:
Aeronautical Engineering Department, King Abdulaziz UniversityJeddah, Saudi Arabia
*
[email protected]
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Abstract

This paper presents the optimum design of a PID controller for the Adaptive Torsion Wing (ATW) using the genetic algorithm (GA) optimiser. The ATW is a thin-wall, two-spar wingbox whose torsional stiffness can be adjusted by translating the spar webs in the chordwise direction inward and towards each. The reduction in torsional stiffness allows external aerodynamic loads to deform the wing and maintain its shape. The ATW is integrated within the wing of a representative UAV to replace conventional ailerons and provide roll control. The ATW is modelled as a two-dimensional equivalent aerofoil using bending and torsion shape functions to express the equations of motion in terms of the twist angle and plunge displacement at the wingtip. The full equations of motion for the ATW equivalent aerofoil were derived using Lagrangian mechanics. The aerodynamic lift and moment acting on the aerofoil were modelled using Theodorsen’s unsteady aerodynamic theory. The equations of motion are then linearised around an equilibrium position and the GA is employed to design a PID controller for the linearised system to minimise the actuation power require. Finally, the sizing and selection of a suitable actuator is performed.

Type
Research Article
Information
The Aeronautical Journal , Volume 119 , Issue 1217 , July 2015 , pp. 871 - 889
Copyright
Copyright © Royal Aeronautical Society 2015

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References

1.Ajaj, R.M., Friswell, M.I., Dettmer, W.G., Allegri, G. and Isikveren, A.Performance and control optimization of a UAV using the adaptive torsion wing, Aeronaut J, October 2012, 116, (1184).CrossRefGoogle Scholar
2.Ajaj, R.M., Friswell, M.I., Dettmer, W.G., Allegri, G. and Isikveren, A.T. Dynamic modelling and actuation of the adaptive torsion wing, J Intelligent Material Systems and Structures (JIMSS), Accepted, 2012.CrossRefGoogle Scholar
3.Theodorsen, T. General Theory of Aerodynamic Instability and the Mechanism of Flutter, Technical Report No. 496, NACA, 1935.Google Scholar
4.Brunton, S.L. and Rowley, C.W.Low-dimensional State-Space Representations for Classical Unsteady Aerodynamic Models, 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Orlando, Florida, USA, 2011, AIAA-2011-476.CrossRefGoogle Scholar
5.Breuker, R.D., Abdallah, M., Milanese, A. and Marzocca, P.Optimal Control of Aeroelastic Systems using Synthetic Jet Actuators, 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Illinois, USA, 2008, AIAA-2008-1726.CrossRefGoogle Scholar
6.Minorsky, N.Directional stability of automatically steered bodies, J American Society of Naval Eng, 1922, 34, p 284.Google Scholar
7.Astrom, K.J. and T. Hagglund, T.PID controllers: theory, design, and tuning, Research Triangle Park, NC: Instrument Society of America, 1995.Google Scholar
8.Chipperfield, A.J. and Fleming, P.J. The Matlab Genetic Algorithm Toolbox, IEE Colloquium on Applied Control Techniques using Matlab, Digest No.1995/014, January 1996.Google Scholar
9.Huber, J.E., Fleck, N.A. and Ashby, M.F. The Selection of Mechanical Actuators Based on Performance Indices, Proceeding of the Royal Society, Part A, 453, pp 2185–2205, 1997.CrossRefGoogle Scholar