Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T11:43:25.645Z Has data issue: false hasContentIssue false

Synthesis of an active flutter suppression system in the transonic domain using a computational model

Published online by Cambridge University Press:  20 May 2021

R. Vepa*
Affiliation:
School of Engineering and Material Science Queen Mary University of LondonLondonE14NSUK
J.R. Kwon
Affiliation:
Aerospace Technology Research Institute Agency for Defense Development Daejeon, 34186Republic of Korea

Abstract

Control laws for implementing active flutter suppression are generally derived from linear aeroelastic models. In this paper, families of control laws for implementing an active flutter suppression system were initially designed using linearised aeroelastic models based on the doublet lattice method after ignoring the aerodynamic loads associated with relatively faster time scales. Using these preliminary sets of control laws and the nonlinear transonic small disturbance theory, near-optimum control laws were chosen in the transonic domain to maximally increase the flutter speed of a typical aircraft wing by at least 16% or more. Thus it is shown that it is feasible to systematically design near-optimal control laws for active flutter suppression using computational models in transonic flow. The doublet lattice method coupled with the zeroth-order matrix Padé approximant provided the fastest method for synthesising a large number of preliminary control laws. The methodology was successfully demonstrated by applying it to two benchmarking examples.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Mykytow, W.J. A brief overview of transonic flutter problems, Unsteady Airloads in Separated and Transonic Flow, AGARD-CP-226, North Atlantic Treaty Organization, 1977.Google Scholar
Bendiksen, O.O. Review of unsteady transonic aerodynamics: Theory and applications. Prog. Aerosp. Sci., 2011, 47 (2), pp 135167.CrossRefGoogle Scholar
Roger, K.L., Hodges, G.E. and Felt, L. Active flutter suppression - a flight test demonstration, J. Aircr., 1975, 12 (6), pp 551556.CrossRefGoogle Scholar
Lyons, M.G., Vepa, R., McIntosh, S.C. and Debra, D.B. Control Law Synthesis and Sensor Design for Active Flutter Suppression, AIAA Paper No. 73–832, Proceedings on the Guidance and Control Conference, Key Biscayne, FL, USA. 20–22 August 1973.CrossRefGoogle Scholar
Vepa, R. Finite state modelling of aeroelastic system. NASA CR-2779, February 1977.Google Scholar
Vepa, R. On the use of Padé approximants to represent aerodynamic loads for arbitrary small motions of wings. Presented at AIAA 14th. Aerospace Sci. Meet., January, 1976, Washington, DC.Google Scholar
Nissim, E. Flutter Suppression Using Active Controls Based on the Concept of Aerodynamic Energy, NASA TN D-6199, 1971.Google Scholar
Nissim, E. Recent Advances in Aerodynamic Energy Concept for Flutter Suppression and Gust Alleviation Using Active Controls, NASA TN D-8519, 1977.Google Scholar
Nissim, E., Caspi, A. and Lottatti, I. Application of the Aerodynamic Energy Concept to Flutter Suppression and Gust Alleviation by use of Active Controls, NASA TP 1137, 1978.CrossRefGoogle Scholar
Nissim, E. and Abel, I. Development and Application of an Optimization Procedure for Flutter Suppression Using the Aerodynamic Energy Concept, NASA TP 1137, 1978.Google Scholar
Nissim, E. Design of Control Laws for Flutter Suppression Based on the Aerodynamic Energy Concept and Comparisons With Other Design Methods, NASA TP 3056, 1990.CrossRefGoogle Scholar
Livne, E. Aircraft active flutter suppression: State of the art and technology maturation needs. J. Aircr., 2018, 55 (1), pp 410452, doi: 10.2514/l.c034442.CrossRefGoogle Scholar
Mukhopadhyay, V. Benchmark active control technology: part I. J. Guid. Control Dyn., 2000, 23 (5), pp 913913, doi: 10.2514/2.4631.CrossRefGoogle Scholar
Mukhopadhyay, V. Benchmark active control technology special section: part II. J. Guid. Control Dyn., 23 (6), pp 10931094, 2000, doi: 10.2514/2.4659.CrossRefGoogle Scholar
Mukhopadhyay, V. Benchmark active control technology special section: part III. J Guid. Control Dyn., 2001, 24 (1), pp 146–146. doi: 10.2514/2.4693.CrossRefGoogle Scholar
Mukhopadhyay, V. Transonic flutter suppression control law design and wind-tunnel test results. J. Guid. Control Dyn., 2000, 23 (5). doi: 10.2514/2.4635.CrossRefGoogle Scholar
Scott, R.C., Hoadley, S.T., Wieseman, C.D. and Durham, M.H. The Benchmark Active Controls Technology Model Aerodynamic Data, AIAA 97-0829-CP, January 1997.Google Scholar
Waszak, M.R. Modeling the Benchmark Active Control Technology Wind-Tunnel Model for Active Control Design Applications, NASA/TP-1998-206270, Langley Research Center, Hampton, Virginia. June 1998.Google Scholar
Svoboda, F. and Hromcik, M. Active flutter suppression by means of fixed-order ${H_\infty }$ control: results for the Benchmark Active Control Technology (BACT) wing, 2019 18th European Control Conference (ECC), Naples, Italy, 25–28 June 2019, DOI: 10.23919/ECC.2019.8795733.CrossRefGoogle Scholar
Adams, W.M., Christhilf, D.M., Waszak, M.R., Mukhopadhyay, V. and Srinathkumar, S. Design, test, and evaluation of three active flutter suppression controllers, NASA TM-4338, 1992.Google Scholar
Isogai, K. On the transonic-dip mechanism of flutter of a sweptback wing, AIAA J., 1979, 17 (7), pp 793795.CrossRefGoogle Scholar
Batina, J.T. and Yang, T.Y. Transonic Calculation of Airfoil Stability and Response with Active Controls, AIAA 84-0873, April 1984.CrossRefGoogle Scholar
Guruswamy, G.P., Tu, E.L. and Goorjian, P.M. Transonic Aeroelasticity of Wings with Active Control Surfaces, AIAA 87-0709-CP, April 1987.CrossRefGoogle Scholar
Guruswamy, G.P. and Tu, E.L. Transonic aeroelasticity of fighter wings with active control surfaces. AIAA J., 1989, 26 (7), pp 682684.Google Scholar
Guruswamy, G.P. Integrated approach for active coupling of structures and fluids. AIAA J., 1988, 27 (6), pp 788793.CrossRefGoogle Scholar
Ominsky, D. and Ide, H. An Effective Flutter Control Method Using Fast, Time-Accurate CFD Codes, AIAA 89-3468-CP, April 1989.Google Scholar
Bendiksen, O.O., Hwang, G. and Piersol, J. Nonlinear Aeroelastic and Aeroservoelastic Calculations for Transonic Wings, AIAA 98-1898, April 1998.CrossRefGoogle Scholar
Silva, W.A. and Bennett, R.M., Investigation of the Aeroelastic Stability of the AFW Wind-Tunnel Model Using CAP-TSD, NASA TM 104142, September 1991.Google Scholar
Stephens, C., Arena, A. and Gupta, K. CFD Based Aeroservoelastic Predictions with Comparisons to Benchmark Experimental Data, AIAA 99-0766, January 1999.CrossRefGoogle Scholar
Djayapertapa, L. and Allen, C.B. Aeroservoelastic Computations in Unsteady Transonic Flow, AIAA 2000-4226, August 2000.CrossRefGoogle Scholar
Djayapertapa, L. and Allen, C.B. Simulation of transonic flutter and active shockwave control. Int. J. Numer. Methods Heat Fluid Flow, 2004, 14 (4), pp 413443, https://doi.org/10.1108/09615530410532231.CrossRefGoogle Scholar
Edwards, J.W. and Thomas, J.L. Computational methods or unsteady transonic flows, NASA TM 8910, 25th AIAA Aerospace Sciences Meeting, 24 March 1987–26 March 1987, Reno, NV, U.S.A., https://doi.org/10.2514/6.1987-107.CrossRefGoogle Scholar
Bennett, R.M. and Edwards, J.W. An Overview of Recent Developments in Computational Aeroelasticity, AIAA 98-2421, 1998.CrossRefGoogle Scholar
Henshaw, M.J.de.C., Badcock, K.J., Vio, G.A., Allen, C.B., Chamberlain, J., Kaynes, I., Dimitriadis, G., Cooper, J.E., Woodgate, M.A., Rampurawala, A.M., Jones, D.P., Fenwick, C.L., Gaitonde, A.L., Taylor, N.V., Amor, D.S. and Eccles, T.A. Nonlinear aeroelastic prediction for aircraft applications. Prog. Aerosp. Sci., 2007, 43 (4), pp 65137.CrossRefGoogle Scholar
Newsom, J.R., Robertshaw, H.H., Kapania, R.K. Control Law Design in a Computational Aeroelasticity Environment, AIAA Paper 2003-1415, 44th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 07 April 2003–10 April 2003, Norfolk, Virginia, https://doi.org/10.2514/6.2003-1415.CrossRefGoogle Scholar
Allen, C.B., Taylor, N.V., Fenwick, C.L., Gaitonde, A.L. and Jones, D.P. A comparison of full non-linear and reduced order aerodynamic models in control law design using a two-dimensional aerofoil model. Int. J. Numer. Methods Eng., 2005, 64 (12), pp 16281648.CrossRefGoogle Scholar
Silva, W.A. and Raveh, D.E. Development of unsteady aerodynamic state-space models from CFD-based pulse responses, in Proc. 42nd AIAA/ASME/ASCE/ASH/ASC Structures, Structural Dynamics, and Materials conference, Seattle, WA, USA, 2001, AIAA Paper 2001-1213.CrossRefGoogle Scholar
Dowell, E.H. and Hall, K.C. Modelling of fluid–structure interaction. Annu. Rev. Fluid Mech., 2001, 33, pp 445490.CrossRefGoogle Scholar
Waite, J.M., Stanford, B.K., Bartels, R.E., Silva, W.A. and Massey, S.J. Active Flutter Suppression Controllers Derived from Linear and Nonlinear Aerodynamics: Application to a Transport Aircraft Model, 2018 Applied Aerodynamics Conference, June 25–29, 2018, Atlanta, Georgia, https://doi.org/10.2514/6.CrossRefGoogle Scholar
Mukhopadhyay, V. Flutter suppression control law design and testing for the active flexible wing. J. Aircr., 1995, 32 (1), pp 4551.CrossRefGoogle Scholar
Zhang, W. and Ye, Z. Control law design for transonic aeroservoelasticity. Aerosp. Sci. Technol., 11, 2007, pp 136145.CrossRefGoogle Scholar
Nie, X., Yang, G. and Zhang, M. Investigation on transonic flutter active suppression with CFD-Based ROMs. Sci. China Phys. Mech. Astron., 2015, 58, pp 110. https://doi.org/10.1007/s11433-014-5440-2.CrossRefGoogle Scholar
Djayapertapa, L., Allen, C.B. and Fiddes, S.P. Two-dimensional transonic aero-servo-elastic computations in the time domain. Int. J. Numer. Methods Eng., 52 (12), pp 13551377.CrossRefGoogle Scholar
Kwon, H-J., Kim, D-H. and Lee, I. Frequency and time domain flutter computations of a wing with oscillating control surface including shock interference effects. Aerosp. Sci. Technol., 2004, 8, pp 519532.CrossRefGoogle Scholar
Yates, E.C. Jr. AGARD Standard Aeroelastic Configuration for Dynamic Response, Candidate Configuration I.-Wing 445.6, NASA TM 100492, 1987.Google Scholar
Harder, R.L. and Desmarais, R.N. Interpolation using surface splines. J. Aircr., 1992, 9 (2), pp 189191.Google Scholar
Rivers, M. NASA CRM Model, https://commonresearchmodel.larc.nasa.gov/fem-file/, Updated September, 2019, Accessed online March, 2020.Google Scholar
Cunningham, H.J., Batina, J.T. and Bennett, R.M., Modern wing flutter analysis by computational fluid dynamics methods. J. Aircr., 1988, 25 (10), pp 962968.CrossRefGoogle Scholar
Lai, K.L. and Lum, K-Y. A Modeling and Simulation Framework for Transonic Flutter Analysis, 19th Australasian Fluid Mechanics Conference, Melbourne, Australia, 8–11 December 2014.Google Scholar
Dowell, E.H., Edwards, J.W. and Strganac, T. Nonlinear aeroelasticity. J. Aircr., 2003, 40 (5), pp 857874.CrossRefGoogle Scholar
Allen, C.B., Jones, D.P., Taylor, N.V., Badcock, K.J., Woodgate, M.A., Rampurawala, A.M., Cooper, J.E. and Vio, G.A. A Comparison of Linear and Non-Linear Flutter Prediction Methods: A Summary of PUMA DARP Aeroelastic Results, Royal Aeronautical Society Aerodynamics Conference, London, 2004.Google Scholar
Lee-Rausch, E.M. and Batina, J.T. Wing flutter boundary prediction using unsteady Euler aerodynamic method. J. Aircr., 1995, 32 (2), pp 416422.CrossRefGoogle Scholar