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Periodic controllers for vibration reduction using actively twisted blades

Published online by Cambridge University Press:  08 July 2016

Claudio Brillante ,
Marco Morandini  and
Paolo Mantegazza
Claudio Brillante
Affiliation:
Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Milano, Italy
Marco Morandini*
Affiliation:
Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Milano, Italy
Paolo Mantegazza
Affiliation:
Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano, Milano, Italy
*
marco.morandini@polimi.it
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Abstract

This paper compares two periodic control methods, the optimal H2 and the periodic static output feedback (POF), to reduce the helicopter rotor vibrations. Actively twisted blades with Macro-Fibre Composite (MFC) piezoelectric actuators are used. The design model is based on a simplified aerodynamic model and on a multi-body model of the Bo 105 isolated rotor with the original blades replaced by actively twisted ones. The performance of the two controllers in alleviating hub loads is verified with improved simulations based on a free-wake model.

Keywords

Active twist rotorperiodic controlvibration controlfree wake
Type
Research Article
Information
The Aeronautical Journal , Volume 120 , Issue 1233 , November 2016 , pp. 1763 - 1784
Copyright
Copyright © Royal Aeronautical Society 2016 

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References

REFERENCES

1. Patt, D., Chandrasekar, J., Bernstein, D.S. and Friedmann, P.P. Higher-harmonic-control algorithm for helicopter vibration reduction revisited, J Guidance, Control and Dynamics, 2005, 28, (5), pp 918–930.CrossRefGoogle Scholar
2. Wilbur, M.L. and Wilkie, W.K. Active-Twist Rotor Control Applications for UAVs, Tech Rep, 2004, U.S. Army Research Laboratory Vehicle Technology Directorate.Google Scholar
3. Mander, A., Feszty, D. and Nitzsche, F. Active pitch link actuator for impedance control of helicopter vibration, American Helicopter Society 64th Annual Forum, 29 April-1 May 2008, Montréal, Québec, Canada.Google Scholar
4. Padthe, A.K. and Friedmann, P.P. Simultaneous BVI noise and vibration reduction in rotorcraft using microflaps including the effect of actuator saturation, American Helicopter Society 68th Annual Forum, 1-3 May 2012, Ft. Worth, Texas, US.Google Scholar
5. Ravichandran, K., Chopra, I., Wake, B.E. and Hein, B. Active pitch link actuator for impedance control of helicopter vibration, American Helicopter Society 67th Annual Forum, 2011, Virginia Beach, Virginia, US.Google Scholar
6. Pawar, P.M. and Jung, S.N. Active twist control methodology for vibration reduction of a helicopter with dissimilar rotor system, Smart Materials and Structures, 2009, 18, (3), p 035013.CrossRefGoogle Scholar
7. Althoff, M., Patil, M.J. and Traugott, J.P. Nonlinear modeling and control design of active helicopter blades, J. American Helicopter Society, 2012, 57, (1), pp 1-11.CrossRefGoogle Scholar
8. Monner, H.P., Riemenschneider, J., Opitz, S. and Schulz, M. Development of active twist rotors at the German Aerospace Center (DLR), 52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 4-7 April 2011, AIAA 2011-1824, Denver, Colorado, US.CrossRefGoogle Scholar
9. Riemenschneider, J. and Opitz, S. Measurement of twist deflection in active twist rotor, Aerospace Science and Technology, 2011, 15, (3), pp 216-223.CrossRefGoogle Scholar
10. Vaghi, R. Studio Numerico del Controllo Ottimo di un Rotore Articolato di Elicottero con Applicazione alle Instabilità di Flappeggio e Ritardo, Master Thesis, 1991, Politecnico di Milano, Dipartimento di Ingegneria Aerospaziale.Google Scholar
11. Arcara, P., Bittanti, S. and Lovera, M. Periodic control of helicopter rotors for attenuation of vibrations in forward flight, IEEE Transaction on Control Systems Technology, 2000, 8, (6), pp 883-894.CrossRefGoogle Scholar
12. Bittanti, S. and Cuzzola, F.A. Periodic active control of vibrations in helicopters: a gain-scheduled multi-objective approach, Control Engineering Practice, 2002, 10, (10), pp 1043-1057.CrossRefGoogle Scholar
13. Ulker, F.D. A New Framework For Helicopter Vibration Suppression; Time-Periodic System Identification and Controller Design, PhD Thesis, April 2011, Ottawa-Carleton Institute for Mechanical and Aerospace Engineering.Google Scholar
14. Brillante, C., Morandini, M. and Mantegazza, P. H2 periodic control on active twist rotor for vibration reduction, AHS 70th Annual Forum and Technology Display, 20-22 May 2014.Google Scholar
15. Brillante, C., Morandini, M. and Mantegazza, P. Periodic output feedback control for helicopter vibration reduction, International Forum on Aeroelasticity and Structural Dynamics, 28 June-2 July 2015, Montréal, Québec, Canada.Google Scholar
16. Dieterich, O., Götz, J., DangVu, B., Haverdings, H., Masarati, P., Pavel, M., Jump, M. and Massimiliano, G. Adverse rotorcraft-pilot coupling: Recent research activities in Europe, 34th European Rotorcraft Forum (ERF), 16-19 September 2008, Liverpool, UK.Google Scholar
17. Masarati, P., Morandini, M. and Mantegazza, P. An efficient formulation for general-purpose multibody/multiphysics analysis, ASME J. Computational and Nonlinear Dynamics, 2014, 9, (4), p 041001. doi: 10.1115/1.4025628.CrossRefGoogle Scholar
18. Ghiringhelli, G.L., Masarati, P. and Mantegazza, P. Multibody implementation of finite volume C0 beams, AIAA J., 2000, 38, (1), pp 131-138.CrossRefGoogle Scholar
19. Ghiringhelli, G.L., Masarati, P. and Mantegazza, P. Characterisation of anisotropic, non-homogeneous beam sections with embedded piezo-electric materials, J. Intelligent Material Systems and Structures, 1997, 8, (10), pp 842-858.CrossRefGoogle Scholar
20. Morandini, M., Chierichetti, M. and Mantegazza, P. Characteristic behavior of prismatic anisotropic beam via generalized eigenvectors, Int. J. Solids and Structures, 2010, 47, (10), pp 1327-1337.CrossRefGoogle Scholar
21. Brillante, C., Morandini, M. and Mantegazza, P. Characterization of beam stiffness matrix with embedded piezoelectric devices via generalized eigenvectors, Int. J. Solids and Structures, 2015, 59, pp 37-45.CrossRefGoogle Scholar
22. Ghiringhelli, G.L., Masarati, P., Morandini, M. and Muffo, D. Integrated aeroservoelastic analysis of induced strain rotor blades, Mechanics of Advanced Materials and Structures, 2008, 15, pp 291-306.CrossRefGoogle Scholar
23. Leishman, G.J. Principles of Helicopter Aerodynamics, 2nd edn., 2006, Cambridge University Press, New York, New York, US.Google Scholar
24. Abedi, H. Development of Vortex Filament Method for Aerodynamic Loads on Rotor Blades, Master’s Thesis, 2013, Chalmers University of Technology, Department of Applied Mechanics, Gothenburg, Sweden.CrossRefGoogle Scholar
25. Sheng, C., Zhao, Q., Rajmohan, N. and Sankar, L. An unstructured hybrid CFD approach for computing rotor wake flows, 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, 4-7 January 2011, Orlando, Florida, US.CrossRefGoogle Scholar
26. Yongjie, S., Qijun, Z., Feng, F. and Guohua, X. A new single-blade based hybrid CFD method for hovering and forward-flight rotor computation, Chinese J. Aeronautics, 2011, 24, pp 127-135.Google Scholar
27. Amiraux, M. Numerical Simulation and Validation of Helicopter Blade-Vortex Interaction Using Coupled Computational CFD/CSD and Three Levels of Aerodynamic Modeling, PhD Thesis, 2014, University of Maryland, Department of Aerospace Engineering.Google Scholar
28. Betz, A. Schraubenpropeller mit geringstem Energieverlust. Mit einem Zusatz von l. Prandtl, Nachrichten von der Gesellschaft der Wissenschaften zu Gttingen, Mathematisch-Physikalische Klasse, 1919, pp 193-217, URL https://eudml.org/doc/59049.Google Scholar
29. Bisplinghoff, R.L., Ashley, H. and Halfman, R.L. Aeroelasticity, 2013, Dover Publications, Mineola, New York, US.Google Scholar
30. Hansen, M.H., Gaunaa, M. and Madsen, H.A. A Beddoes-Leishman Type Dynamic Stall Model in State-Space and Indicial Formulations, Tech Rep 1354, June 2004, Riso National Laboratory.Google Scholar
31. Vermeer, L.J. A review of wind turbine wake research at TUDelft, 20th 2001 ASME Wind Energy Symposium, Aerospace Sciences Meetings, 2001, AIAA 2001-0030, Reno, Nevada, US.CrossRefGoogle Scholar
32. Johnson, W. Influence of wake models on calculated tiltrotor aerodynamics, American Helicopter Society Aerodynamics, Acoustics, and Test and Evaluation Technical Specialists Meeting, 23-25 January 2002, San Francisco, California, US.Google Scholar
33. Johnson, W. A general free wake geometry calculation for wings and rotors, American Helicopter Society 51st Annual Forum, 9-11 May 1995, Ft. Worth, Texas, US.Google Scholar
34. Leishman, J.G., Bhagwat, M.J. and Ananthan, S. Free-vortex wake predictions of the vortex ring state for single-rotor and multi-rotor configurations, 58th Annual Forum and Technology Display of the American Helicopter Society International, 11-13 June 2002, Montréal, Québec, Canada.Google Scholar
35. MatPy – call Python from MATLAB, http://algoholic.eu/matpy/.Google Scholar
36. Quaranta, G., Masarati, P. and Mantegazza, P. A conservative mesh-free approach for fluid-structure interface problems, International Conference for Coupled Problems in Science and Engineering, 23-29 May 2005, Santorini, Greece.Google Scholar
37. Sa, J.H., Kim, J.W., Park, S.H., You, Y.H., Park, J.S., Jung, S.N. and Yu, Y.H. Prediction of HART II airloads considering fuselage effect and elastic blade deformation, Heli Japan, 1-3 November 2010.Google Scholar
38. Amiraux, M. Numerical Simulation and Validation of Helicopter Blade-Vortex Interaction Using Coupled Computational CFD/CSD and Three Levels of Aerodynamic Modeling, PhD Thesis, 2014, University of Maryland, Department of Aerospace Engineering.Google Scholar
39. Verhaegen, M. and Yu, X. A class of subspace model identification algorithms to identify periodically and arbitrarily time-varying systems, Automatica, 1995, 31, (2), pp 201-216.CrossRefGoogle Scholar
40. Bittanti, S. and Colaneri, P. Periodic Systems Filtering and Control, 2009, Springer, London, UK.Google Scholar
41. Hench, J.J. and Laub, A.J. Numerical solution of the discrete-time periodic Riccati equation, IEEE Transactions on Automatic Control, 1994, 39, (6), pp 1197-1210.CrossRefGoogle Scholar
42. Varga, A. On solving periodic Riccati equations, Numerical Linear Algebra with Applications, 2008, 15, (9), pp 809-835.CrossRefGoogle Scholar
43. Varga, A. and Pieters, S. A computational approach for optimal periodic output feedback control, IEEE International Symposium on Computer Aided Control System Design - CACSD, 1996, Dearborn, Michigan, US, pp 176-181.Google Scholar
44. Varga, A. Periodic lyapounov equations: Some applications and new algorithms, Int. J. Control, 1997, 67, pp 69-88.CrossRefGoogle Scholar
45. Schulz, M. and Riemenschneider, J. Investigation of active twist rotor for blade de-icing, American Helicopter Society 69th Annual Forum, 21-23 May 2013, Phoenix, Arizona, US.Google Scholar
46. Amsallem, D. Interpolation on Manifolds of CFD-Based Fluid and Finite Element-Based Structural Reduced-Order Models for On-Line Aeroelastic Predictions, PhD Thesis, 2010, Stanford University, Department of Aeronautics and Astronautics.Google Scholar
47. Caigny, J.D., Camino, J.F. and Swevers, J. Interpolation-based modeling of MIMO LPV systems, IEEE Transactions on Control Systems Technology, 2011, 19, (1), pp 46-63.CrossRefGoogle Scholar
48. Zhou, K. and Doyle, J.C. Essentials of Robust Control, 1998, Prentice Hall, Upper Saddle River, New Jersey, US.Google Scholar