DOI QR코드

DOI QR Code

Robust market-based control method for nonlinear structure

  • Song, Jian-Zhu (State Key Lab of Coastal and Offshore Engineering, Liaoning Collaborative Innovation Center for Engineering Disaster Prevention and Mitigation, Dalian University of Technology) ;
  • Li, Hong-Nan (State Key Lab of Coastal and Offshore Engineering, Liaoning Collaborative Innovation Center for Engineering Disaster Prevention and Mitigation, Dalian University of Technology) ;
  • Li, Gang (State Key Lab of Coastal and Offshore Engineering, Liaoning Collaborative Innovation Center for Engineering Disaster Prevention and Mitigation, Dalian University of Technology)
  • Received : 2015.12.17
  • Accepted : 2016.04.19
  • Published : 2016.06.25

Abstract

For a nonlinear control system, there are many uncertainties, such as the structural model, controlled parameters and external loads. Although the significant progress has been achieved on the robust control of nonlinear systems through some researches on this issue, there are still some limitations, for instance, the complicated solving process, weak conservatism of system, involuted structures and high order of controllers. In this study, the computational structural mechanics and optimal control theory are adopted to address above problems. The induced norm is the eigenvalue problem in structural mechanics, i.e., the elastic stable Euler critical force or eigenfrequency of structural system. The segment mixed energy is introduced with a precise integration and an extended Wittrick-Williams (W-W) induced norm calculation method. This is then incorporated in the market-based control (MBC) theory and combined with the force analogy method (FAM) to solve the MBC robust strategy (R-MBC) of nonlinear systems. Finally, a single-degree-of-freedom (SDOF) system and a 9-stories steel frame structure are analyzed. The results are compared with those calculated by the $H{\infty}$-robust (R-$H{\infty}$) algorithm, and show the induced norm leads to the infinite control output as soon as it reaches the critical value. The R-MBC strategy has a better control effect than the R-$H{\infty}$ algorithm and has the advantage of strong strain capacity and short online computation time. Thus, it can be applied to large complex structures.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. Aloliwi, B. and Khalil, H.K. (1997), "Robust adaptive output feedback control of nonlinear systems without persistence of excitation", Automatica, 33(11), 2025-2032. https://doi.org/10.1016/S0005-1098(97)00117-9
  2. Baskar, J. and Bradley, R.H. (1994), "An optimization approach to robust nonlinear control design", Int. J. Control, 59(3), 639-664. https://doi.org/10.1080/00207179408923098
  3. Cho, H.C., Jin, W.L., Lee, Y.J. and Lee, K.S. (2008), "Lyapunov theory based robust control of complicated nonlinear mechanical systems with uncertainty", J. Mech. Sci. Technol., 22(11), 2142-2150. https://doi.org/10.1007/s12206-008-0707-z
  4. Hrovat, D., Barak, P. and Rabins, M. (2014), "Semi-active versus passive or active tuned mass dampers for structural control", J. Eng. Mech., 109(3), 691-705. https://doi.org/10.1061/(ASCE)0733-9399(1983)109:3(691)
  5. Huo, L.S. and Li, H.N. (2005), "Control law for market-based semi active tuned liquid column dampers", J. Appl. Mech., 22(1), 71-75.
  6. Katebi, M.R., Grimble, M.J. and Zhang, Y. (1997), "$H{\infty}$ robust control design for dynamic ship positioning", Iee. P-contr. Theor. Appl., 144(2), 110-120. https://doi.org/10.1049/ip-cta:19971030
  7. Kuperman, A. and Zhong, Q.C. (2011), "Robust control of uncertain nonlinear systems with state delays based on an uncertainty and disturbance estimator", Int. J. Robust Nonlin., 21(1), 79-92. https://doi.org/10.1002/rnc.1578
  8. Kushner, H.J. (2006), "Numerical approximations for non-zero-sum stochastic differential games", Siam. J. Control Optim., 46(6), 1942-1971. https://doi.org/10.1137/050647931
  9. Li, G., Liu, Q.F. and Li, H.N. (2011), "Inelastic structural control based on MBC and FAM", Math. Prob. Eng., 11(1): 1-18.
  10. Li, G., Zhang, Y. and Li, H.N. (2014), "Nonlinear seismic analysis of reinforced concrete frames using the force analogy method", Earthq. Eng. Struct., 43(14), 2115-2134. https://doi.org/10.1002/eqe.2439
  11. Li, H.N. and Li, Y. (2008), "Semi-active control for MRD-isolation structure using MBC strategy", J. Earthq. Eng. Vib., 28(5), 140-145.
  12. Lin, T.H. and Pian, T. (1969), "Theory of inelastic structures", J. Appl. Mech., 287(4), 354-355.
  13. Liu, X., Su, H., Yao, B. and Chu, J (2009), "Adaptive robust control of nonlinear systems with dynamic uncertainties", Int. J. Adapt. Control Sig. Proc., 23(4), 353-377. https://doi.org/10.1002/acs.1048
  14. Luo, Y., Sun, Q., Zhang, H. and Cui, L. (2015), "Adaptive critic design-based robust neural network control for nonlinear distributed parameter systems with unknown dynamics", Neurocomputing, 148, 200-208. https://doi.org/10.1016/j.neucom.2013.08.049
  15. Lynch, J.P. and Law, K.H. (2002), "Market-based control of linear structural systems", Earthq. Eng. Struct., 31(10), 1855-1877. https://doi.org/10.1002/eqe.193
  16. Lynch, J.P. and Law, K.H. (2004), "Decentralized energy market-based structural control", Earthq. Eng. Struct., 17(3-4), 557-572.
  17. Marino, R. and Tomei, P. (1997), "Nonlinear control design", Automatica, 33(9), 1769-1770. https://doi.org/10.1016/S0005-1098(97)82237-6
  18. Peng, H., Wu, Z.G. and Zhong, W.X. (2014), "$H_{\infty}$ norm computation of linear continuous-time periodic systems by a structure-preserving algorithm", Int. J. Control, 87(1), 131-142. https://doi.org/10.1080/00207179.2013.823670
  19. Safonov, M.G., Chiang, R.Y. and Flashner, H. (1991), "H (infinity) robust control synthesis for a large space structure", J. Guid., Control, Dyn., 14(3), 513-520. https://doi.org/10.2514/3.20670
  20. Tan, S.J., Wu, Z.G. and Zhong, W.X. (2008), "Optimal induced norm computation of discrete $H_{\infty}$ control systems with time-delays", J. Global. Optim., 40(4), 653-662. https://doi.org/10.1007/s10898-006-9118-9
  21. Wang, C.L. and Lin, Y. (2013), "Robust adaptive neural control for a class of uncertain MIMO nonlinear systems", Int. J. Syst. Sci., 46(11), 1-10.
  22. Wanxie, Z., Williams, F.W. and Bennett, P.N. (1997), "Extension of the Wittrick-Williams algorithm to mixed variable systems", J. Vib. Acoust., 119(3), 334-340. https://doi.org/10.1115/1.2889728
  23. Wong, K.K. (2005), "Predictive optimal linear control of inelastic structures during earthquake. Part II", J. Eng. Mech., 131(2), 142-152. https://doi.org/10.1061/(ASCE)0733-9399(2005)131:2(142)
  24. Wong, K.K. and Zhao, D.F. (2007), "Uncoupling of potential energy in nonlinear seismic analysis of framed structures", J. Eng. Mech., 133(10), 1061-1071. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:10(1061)
  25. Wu, Z.G. and Zhong, W.X. (2009), "A structure-preserving algorithm for the minimum $H_{\infty}$ norm computation of finite-time state feedback control problem", Int. J. Control, 82(4), 773-781. https://doi.org/10.1080/00207170802294639
  26. Zhang, Y.G., Xiang, J. and Xiao, J. (2004), "Decentralized stabilization of continuous-time fuzzy large-scale systems via LMI method", Syst. Eng. Electron., 26(6), 773-776.
  27. Zhao, G.W., Pei, X.Z. and Zhou, X.S. (2006), "The fundamental research on prediction method of structural earthquake response based on energy balance", Ind. Constr., 36(1), 182-187.
  28. Zhong, W.X. (2004), "On precise integration method", J. Comput. Appl. Math., 163(1), 59-78. https://doi.org/10.1016/j.cam.2003.08.053
  29. Zhou, J. and Wen, C. (2011), "Robust adaptive control of uncertain nonlinear systems in the presence of input saturation", Syst. Indent., 56(7), 1672-1678.