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Generalized composite noncertainty-equivalence adaptive control of a prototypical wing section with torsional nonlinearity

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Abstract

The paper presents a generalized composite noncertainty-equivalence adaptive control system for the control of a prototypical aeroelastic wing section using a single trailing-edge control surface. The plunge–pitch (two-degree-of-freedom) dynamics of this aeroelastic system include torsional pitch-axis nonlinearity. The open-loop system exhibits limit cycle oscillations beyond a critical free-stream velocity. It is assumed that parameters of the model are not known. The objective is to suppress the oscillatory responses of the system. Based on the immersion and invariance approach, a generalized composite noncertainty-equivalence adaptive (NCEA) control system for regulation of the pitch angle is designed. The control system consists of a control module and a composite parameter identifier—designed independently. The composite integral parameter estimation law is based on (1) the immersion and invariance (I&I) theory, (2) gradient-based adaptation algorithm, and (3) classical certainty-equivalence adaptive (CEA) update rule. Besides the composite integral component, the full parameter estimate also includes a judiciously chosen nonlinear algebraic function. This composite identifier inherits stronger stability properties. Using the Lyapunov analysis, asymptotic suppression of the limit cycle oscillations and the boundedness of system trajectories are established. Interestingly, in the closed-loop system including the composite update rule, there exist two attractive manifolds to which the system’s trajectories converge. Simulation results are presented which show the suppression of the oscillatory plunge displacement and pitch angle responses despite uncertainties in the model parameters. Furthermore, the performance and stability properties of this composite NCEA control system—including the gradient-based adaptation and the update rule of the CEA system—are better than the simple NCEA system.

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Abbreviations

a :

Nondimensionalized distance from the midchord to the elastic axis

b :

Semichord of the wing

\(c_h\) :

Structural damping coefficient in plunge due to viscous damping

\(c_\alpha \) :

Structural damping coefficient in pitch due to viscous damping

\(k_{1}, (\gamma _g,\Gamma )\) :

Feedback gain, adaptation gains

h :

plunge displacement

\(I_\alpha \) :

Mass moment of inertia of the wing about the elastic axis

\(k_h\) :

Structural spring constant in plunge

\(k_{\alpha _i}\) :

Structural spring constants in pitch

\(m_t\) :

Mass of the plunge–pitch system

\(m_w\) :

Mass of the wing

\(M_s, M_d, B_0, g_0,b_0 \) :

System matrices

ML :

Moment and lift

\(s_p\), s :

Span, \(\dot{{\tilde{\alpha }}}+\lambda _1 {\tilde{\alpha }}\)

U, u :

Free-stream velocity and flap deflection

\(V_g, V_c\) :

Lyapunov functions

x :

State vector (\(h, \alpha , \dot{h}, {\dot{\alpha }})^T\)

\(x_\alpha \) :

Nondimensionalized distance measured from the elastic axis to the center of mass

z :

Parameter error \({\hat{\theta }}-\theta \)

\(\alpha \), \(\alpha _r\), \(\tilde{\alpha }\) :

Pitch angle, reference angle, \(\alpha -\alpha _r\)

\(u=\beta ,\) \(\beta _f\) :

Flap deflection angle, filtered \(\beta \)

\((\phi , W)\), \(\phi _f\) :

Regressor vectors, filtered \(\phi \)

\(\lambda _1\), (\(\lambda _f\), \(k_f\)):

Gain in s, filter parameters

\(\mu \) :

Algebraic component of \({\hat{\theta }}\)

\(\rho \) :

Density of air

\(\theta \) :

Unknown parameter vector

\({\hat{\theta }}\), \(\hat{\theta }_{Igc}\) :

Estimate of \(\theta \), integral part of \({\hat{\theta }}\)

References

  1. Lee, B.H.K., Price, S.J., Wong, Y.S.: Nonlinear aeroelastic analysis of airfoils: bifurcation and chaos. Prog. Aerosp. Sci. 35(3), 205–334 (1999). https://doi.org/10.1016/S0376-0421(98)00015-3

    Article  Google Scholar 

  2. Thomas, J.P., Dowell, E.H., Hall, K.C.: Nonlinear inviscid aerodynamic effects on transonic divergence. Flutter Limit-Cycle Oscil. AIAA J. 40(4), 638–646 (2002)

    Google Scholar 

  3. Gilliatt, H.C., Strganac, T.W., Kurdila, A.J.: An investigation of internal resonance in aeroelastic systems. Nonlinear Dyn. 31(1), 1–22 (2003). https://doi.org/10.1023/A:1022174909705

    Article  MATH  Google Scholar 

  4. Marzocca, P., Librescu, L., Silva, W.A.: Flutter, postflutter, and control of a supersonic wing section. J. Guid. Control Dyn. 25(5), 962–970 (2002)

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Waszak, M.R.: Robust multivariable flutter suppression for benchmark active control technology wind-tunnel model. J. Guid. Control Dyn. 24(1), 147–153 (2001)

    Article  Google Scholar 

  7. Mukhopadhyay, V.: Transonic flutter suppression control law design and wind-tunnel test results. J. Guid. Control Dyn. 23(5), 930–937 (2000)

    Article  Google Scholar 

  8. Kelkar, A.G., Joshi, S.M.: Passivity-based robust control with application to benchmark controls technology wing. J. Guid. Control Dyn. 23(5), 938–947 (2000)

    Article  Google Scholar 

  9. Barker, J.M., Balas, G.J.: Comparing linear parameter- varying gain scheduled control techniques for active flutter suppression. J. Guid. Control Dyn. 23(5), 948–955 (2000)

    Article  Google Scholar 

  10. Guillot, D.M., Friedmann, P.P.: Fundamental aeroservoelastic study combining unsteady computational fluid mechanics with adaptive control. J. Guid. Control Dyn. 23(6), 1117–1126 (2000)

    Article  Google Scholar 

  11. Scott, R.C., Pado, L.E.: Active control of wind-tunnel model aeroelastic response using neural networks. J. Guid. Control Dyn. 23(6), 1100–1108 (2000)

    Article  Google Scholar 

  12. Shukla, H., Patil, M.J.: Nonlinear state feedback control design to eliminate subcritical limit cycle oscillations in aeroelastic systems. Nonlinear Dyn. 88, 1599–1614 (2017)

    Article  Google Scholar 

  13. Ko, J., Kurdila, A.J., Strganac, T.W.: Nonlinear control of a prototypical wing section with torsional nonlinearity. J. Guid. Control Dyn. 20(6), 1181–1189 (1997)

    Article  Google Scholar 

  14. Sheta, E.F., Harrand, V.J., Thompson, D.E., Strganac, T.W.: Computational and experimental investigation of limit cycle oscillations of nonlinear aeroelastic systems. J. Aircr. 39(1), 133–141 (2002)

    Article  Google Scholar 

  15. Block, J.J., Strganac, T.W.: Applied active control for a nonlinear aeroelastic structure. J. Guid. Control Dyn. 21(6), 838–845 (1998)

    Article  Google Scholar 

  16. Platanitis, G., Strganac, T.W.: Control of a nonlinear wing section using leading- and trailing-edge surfaces. J. Guid. Control Dyn. 27(1), 52–58 (2004)

    Article  Google Scholar 

  17. Xing, W., Singh, S.N.: Adaptive output feedback control of a nonlinear aeroelastic structure. J. Guid. Control Dyn. 23(6), 1109–1116 (2000)

    Article  Google Scholar 

  18. Behal, A., Marzocca, P., Rao, V.M., Gnann, A.: Nonlinear adaptive control of an aeroelastic two-dimensional lifting surface. J. Guid. Control Dyn. 29(2), 382–390 (2006)

    Article  Google Scholar 

  19. Gujjula, S., Singh, S.N., Yim, W.: Adaptive and neural control of a wing section using leading- and trailing-edge surfaces. Aerosp. Sci. Technol. 9(2), 161–171 (2005)

    Article  Google Scholar 

  20. Behal, A., Rao, V.M., Marzocca, P., Kamaludeen, M.: Adaptive control for a nonlinear wing section with multiple flaps. J. Guid. Control Dyn. 29(3), 744–749 (2006)

    Article  Google Scholar 

  21. Reddy, K.K., Chen, J., Behal, A., Marzocca, P.: Multi-input/multi-output adaptive output feedback control design for aeroelastic vibration suppression. J. Guid. Control Dyn. 30(4), 1040–1048 (2007)

    Article  Google Scholar 

  22. Lee, K.W., Singh, S.N.: \(L_1\) adaptive control of a nonlinear aeroelastic system despite gust load. J. Vib. Control 19(12), 1807–1821 (2013)

    Article  Google Scholar 

  23. Zhang, K., Wang, Z., Behal, A.: Marzocca: novel nonlinear control design for a two-dimensional airfoil under unsteady flow. J. Guid. Control Dyn. 36(6), 1681–1694 (2013)

    Article  Google Scholar 

  24. Wang, Z., Behal, A., Marzocca, P.: Model-free control design for multi-input multi-output aeroelastic system subject to external disturbance. J. Guid. Control Dyn. 34(2), 446–458 (2011)

    Article  Google Scholar 

  25. Chen, C.L., Chang, C.W., Yau, H.T.: Terminal sliding mode control for aeroelastic systems. Nonlinear Dyn. 70, 2015–2026 (2012)

    Article  MathSciNet  Google Scholar 

  26. Ioannou, P.A., Sun, J.: Stable and Robust Adaptive Control, pp. 85–134. Prentice-Hall, Upper Saddle River (1995)

  27. Astolfi, A., Karagiannis, D., Ortega, R.: Nonlinear and Adaptive Control with Applications, pp. 276–309. Springer, London (2008)

  28. Seo, D., Akella, M.R.: High-performance spacecraft attitude- tracking control through attracting-manifold design. J. Guid. Control Dyn. 31(4), 884–891 (2008). https://doi.org/10.2514/1.33308

    Article  Google Scholar 

  29. Lee, K.W., Singh, S.N.: Non-certainty-equivalence adaptive control of a nonlinear aeroelastic system. Int. J. Electr. Telecommun. 56, 463–471 (2010)

    Article  Google Scholar 

  30. Lee, K.W., Singh, S.N.: Multi-Input Noncertainty-Equivalent Adaptive Control of an Aeroelastic System. J. Guid. Control Dyn. 33(5), 1451–1460 (2010). https://doi.org/10.2514/1.48302

    Article  Google Scholar 

  31. Mannarino, A., Mantegazza, P.: Multifidelity control of aeroelastic systems: an immersion and invariance approach. J. Guid. Control Dyn. 37(5), 1568–1582 (2014)

    Article  Google Scholar 

  32. Duarte, M.A., Narendra, K.S.: Combined direct and indirect approach to adaptive control. IEEE Trans. Autom. Control 34(10), 1071–1075 (1989)

    Article  MathSciNet  Google Scholar 

  33. Slotine, J.-J.E., Li, W.: Composite adaptive control of robot manipulators. Automatica 25(4), 509–519 (1989)

    Article  MathSciNet  Google Scholar 

  34. Patre, P.M., Bhasin, S., Wilcox, Z.D., Dixon, W.E.: Composite adaptation for neural network-based controllers. IEEE Trans. Autom. Control 55(4), 944–950 (2010)

    Article  MathSciNet  Google Scholar 

  35. Lavretsky, E.: Combined/composite model reference adaptive control. IEEE Trans. Autom. Control 54(11), 2692–2697 (2009)

    Article  MathSciNet  Google Scholar 

  36. Liu, Z., Yuan, R., Fan, G., Yi, J.: Immersion and invariance based composite adaptive control of nonlinear high-order systems. In Proceedings of 2018 Chinese Control and Decision Conference, IEEE, pp. 96–101 (2018)

  37. Lee, K.W., Singh, S.N.: Generalized Composite Noncertainty-Equivalence Adaptive Control of Orbiting Spacecraft in Vicinity of Asteroid. J. Astronaut. Sci. 67(3), 1021–1043 (2020)

    Article  Google Scholar 

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Correspondence to Sahjendra N. Singh.

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Appendix

Appendix

System parameters

$$\begin{aligned}&\!\!\!b = 0.135[\hbox {m}], m_w = 2.049[\hbox {kg}], \\&\!\!\!c_h = 27.43[\hbox {Ns/m}], c_{\alpha }=0.036[\hbox {Ns}]\\&\!\!\!\rho = 1.225[\hbox {kg}/\hbox {m}^3], c_{l \alpha } = 6.28, c_{l \beta }=3.358, \\&\!\!\!c_{m \alpha }=(0.5+a) c_{l \alpha }\\&\!\!\!c_{m \beta }=-0.635, m_t = 12.387[\hbox {kg}],\\&\!\!\!I_{\alpha }=0.0517+m_wx_{\alpha }^2b^2 [\hbox {kg} \cdot \hbox {m}^2]\\&\!\!\!x_{\alpha } = [0.0873 - (b + ab)]/b\\&\!\!\!k_{\alpha }=2.82*(1-22.1\alpha \\&\qquad +1315.5 \alpha ^2 -8580 \alpha ^3 +17289.7 \alpha ^4)[\hbox {N} \cdot \hbox {m/rad}]\\&\!\!\!k_{h0}=2844.4[\hbox {N/m}].\\ \end{aligned}$$

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Lee, K.W., Singh, S.N. Generalized composite noncertainty-equivalence adaptive control of a prototypical wing section with torsional nonlinearity. Nonlinear Dyn 103, 2547–2561 (2021). https://doi.org/10.1007/s11071-021-06227-3

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