Skip to main content
SpringerLink
Log in

A reduced-order-model-based multiple-in multiple-out gust alleviation control law design method in transonic flow

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

Gust alleviation is very important to a large flexible aircraft. A nonlinear low-order aerodynamic state space model is required to model the nonlinear aeroelastic responses due to gust. Based on the proper orthogonal decomposition method, a reduced order modeling of gust loads was proposed. And then the open-loop and closed-loop reduced order state space model for the transonic aeroelastic system was developed. The static output feed back control scheme was used to design a simple multiple-in multiple-out (MIMO) gust alleviation control law. The control law was demonstrated with the Goland+ wing model with four control surfaces. The simulation results of different discrete gusts show the capability and good performance of the designed MIMO controller in transonic gust alleviation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Code of Federal Regulations, Aeronautics and Space, Part 25.341. Gust and turbulence loads. Maryland: Office of Federal Register, National Archives and Records Administration, January 2003

    Google Scholar 

  2. Robert C, Michael J A, Ryan P D, et al. Fight test of the f/a-18 active aeroelastic wing airplane. NASA/TM-2005-213664, 2005.

    Google Scholar 

  3. Simpson J, Suleman A, Cooper J. Review of European research project active aeroelastic aircraft structures. In: IFASD Conference, Munich, 2005

  4. Gur O, Bhatia M, Schetz J, et al. Design optimization of a truss-braced-wing transonic transport aircraft. J Aircraft, 2010, 47(6): 1907–1917

    Article  Google Scholar 

  5. Moulin B, Karpel M. Gust loads alleviation using special control surfaces. J Aircraft, 2007, 44(1): 17–24

    Article  Google Scholar 

  6. Vartio E J, Shaw E E, Vetter T. Gust load alleviation flight control system design for a sensorcraft vehicle. AIAA 2008-7192, 2008

    Google Scholar 

  7. Shao K, Wu Z, Yang C, et al. Design of an adaptive gust response alleviation control system: simulations and experiments. J Aircraft, 2010, 47(3): 1022–1029

    Article  Google Scholar 

  8. Ricci S, Scotti A. Gust response alleviation on flexible aircraft using multi-surface control. AIAA 2010-3117, 2010

    Google Scholar 

  9. Zeng J, Moulin B, Callafon R. Adaptive feed-forward control for gust load alleviation. J Guid Control Dynam, 2010, 33(3): 862–872

    Article  Google Scholar 

  10. Christopher D R, Christine V J. Survey of applications of active control technology for gust alleviation and new challenges for lighter-weight aircraft. NASA/TM-2012-216008, 2012

    Google Scholar 

  11. Raveh D E. CFD-based models of aerodynamic gust response. J Aircraft, 2007, 44(3): 888–897

    Article  Google Scholar 

  12. Raveh D E. Gust-response analysis of free elastic aircraft in the transonic flight regime. J Aircraft, 2011, 48(4): 1204–1211

    Article  Google Scholar 

  13. Robert G C, Rafael P, Paul G. Robust gust alleviation and stabilization of very flexible aircraft. AIAA J, 2013, 51(2): 330–340

    Article  Google Scholar 

  14. Robert E B. Development, verification and use of gust modeling in the NASA computational fluid dynamics code fun3d. NASA/TM-2012-217771, 2012

    Google Scholar 

  15. Silva W A. Identification of nonlinear aeroelastic systems based on the volterra theory: progress and opportunities. Nonl Dyn, 2005, 39: 25–62

    Article  MATH  Google Scholar 

  16. Chen G., Zuo Y, Sun, J, et al. Support-vector-machine-based reduced-order model for limit cycle oscillation prediction of nonlinear aeroelastic system. Math Probl Eng, doi:10.1155/2012/152123, 2012

    Google Scholar 

  17. Lieu T, Farhat C. Adaptation of aeroelastic reduced-order models and application to an f-16 configuration. AIAA J, 2007, 45(6): 244–1257

    Google Scholar 

  18. Beran P S, Lucia D J. A reduced order cyclic method for computation of Limit Cycles. Nonl Dyn, 2005, 39: 143–158

    Article  MATH  Google Scholar 

  19. Gaetan K, Jean-claude G, Alexander F W, et al. The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview. Nonl Dyn, 2005, 41: 147–169

    Article  MATH  Google Scholar 

  20. Custer C H, Thomas J P, Dowell E H, et al. A nonlinear harmonic balance method for the cfd code OVERFLOW 2. International Forum on Aeroelasticity and Structural Dynamics, 2009-050, Seattle, 2009

    Google Scholar 

  21. Badcock K J, Woodgate M A. Bifurcation prediction of large-order aeroelastic models. AIAA J, 2010, 48(6): 1037–1046

    Article  Google Scholar 

  22. Chen G, Li Y M, Yan G R. A nonlinear pod reduced order model for limit cycle oscillation prediction. Sci China Phys Mech Astron, 2010, 53(6): 1325–1332

    Article  Google Scholar 

  23. Chen G, Li Y M, Yan G R. Active control stability/augmentation system design based on reduced order model. Chin J Aeronaut, 2010, 23(6): 637–644

    Google Scholar 

  24. Chen G, Li Y M, Yan G R. Limit cycle oscillation prediction and control design method for aeroelastic system based on new nonlinear reduced order model. Int J Comput Meth, 2011, 8(1): 77–90

    Article  MATH  MathSciNet  Google Scholar 

  25. Chen G, Sun J, Li Y M. Active flutter suppression control law design method based on balanced proper orthogonal decomposition reduced order model. Nonl Dyn, 2012, 70: 1–12

    Article  MathSciNet  Google Scholar 

  26. Chen G, Sun J, Li Y M. Adaptive reduced-order-model-based control law design for active flutter suppression. J Aircraft, 2012, 49(4): 973–980

    Article  MathSciNet  Google Scholar 

  27. Zaide A, Raveh D E. Numerical simulation and reduced-order modeling of airfoil gust response. AIAA J, 2006, 44(8): 1826–1834

    Article  Google Scholar 

  28. Sohrab H, Hugh H T L, Joaquim R R A. A model-predictive gust load alleviation controller for a highly flexible aircraft. J Guid Control Dynam, 2012, 36(6): 1751–1766

    Google Scholar 

  29. Ronch A D, Badcock K J, Wang Y, et al. Nonlinear model reduction for flexible aircraft control design. AIAA -2012-4404, 2012

    Google Scholar 

  30. Mukhopadhyay V. Historical perspective on analysis and control of aeroelastic responses. J Guid Control Dynam, 2003, 26(5): 673–684

    Article  Google Scholar 

  31. Kumar V S, Laura A M, Raymond K, et al. Receptance based active aeroelastic control using multiple control surfaces. AIAA-2012-1485, 2012

    Google Scholar 

  32. Karpel M, Moulin B, Presente E, et al. Dynamic gust loads analysis for transport aircraft with nonlinear control effects. AIAA-2008-1994, 2008

    Google Scholar 

  33. Lesoinne M, Sarkis M, Hetmaniuk U, et al. A linearized method for the frequency analysis of three-dimensional fluid/structure interaction problems in all flow regime. Comput Meh Appl Mech Eng, 2001, 190: 3121–3146

    Article  MATH  Google Scholar 

  34. Holmes P, Lumley J L, Berkooz G. Turbulence, Coherent Structures, Dynamical Systems and Symmetry. Cambridge: Cambridge University Press, 1996

    Book  MATH  Google Scholar 

  35. Singh R, Baeder J D. Direct calculation of three-dimensional indicial lift response using computational fluid dynamics. J Aircraft, 1997, 34(4): 465–471

    Article  Google Scholar 

  36. Bartels R E. Uncertainty due to fluid/structure interaction for the aeroelastic vehicle traversing the transonic regime. AIAA-2012-1631, 2012

    Google Scholar 

  37. Wang Z, Zhang Z, Chen P C, et al. A compact cfd-based reduced order modeling for gust analysis. AIAA-2011-2041, 2011

    Google Scholar 

  38. Eastep F E, Olsen J J. Transonic flutter analysis of a rectangular wing with conventional airfoil sections. AIAA J, 1980, 18(10): 1159–1164

    Article  Google Scholar 

  39. Beran P S, Strganac T W, Kim K, et al. Studies of store-induced limit-cycle oscillations using a model with full system nonlinearities. Nonlinear Dynam, 2004, 37: 329–339

    Article  Google Scholar 

  40. Ali H N, Mehdi G., Hajj LR. Normal form representation of the aeroelastic response of the Goland wing. Nonl Dyn, 2012, 67: 1847–1861

    Article  MATH  Google Scholar 

  41. Mayuresh J P, Dewey H H. Output feedback control of the nonlinear aeroelastic response of a slender wing. J Guid Control Dynam, 1992, 25(2):302–308

    Google Scholar 

  42. Syrmos V L, Abdallah C T, Dorato P, et al. Static output feedback: A survey. Automatica, 1997, 33(2):125–137

    Article  MATH  MathSciNet  Google Scholar 

  43. Jacob E, Arie W. A result on output feedback linear quadratic control. Automatica. 2008, 44: 265–271

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an, 710049, China

    Gang Chen, Xian Wang & YueMing Li

Authors
  1. Gang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xian Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. YueMing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gang Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, G., Wang, X. & Li, Y. A reduced-order-model-based multiple-in multiple-out gust alleviation control law design method in transonic flow. Sci. China Technol. Sci. 57, 368–378 (2014). https://doi.org/10.1007/s11431-013-5416-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-013-5416-x

Keywords

Search

Navigation