Smart Structures and Systems

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A model-based adaptive control method for real-time hybrid simulation

  • Xizhan Ning (College of Civil Engineering, Huaqiao University) ;
  • Wei Huang (College of Civil Engineering, Huaqiao University) ;
  • Guoshan Xu (School of Civil Engineering, Harbin Institute of Technology) ;
  • Zhen Wang (School of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Lichang Zheng (School of Civil Engineering, Harbin Institute of Technology)
  • Received : 2022.07.22
  • Accepted : 2023.03.03
  • Published : 2023.05.25
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Abstract

Real-time hybrid simulation (RTHS), which has the advantages of a substructure pseudo-dynamic test, is widely used to investigate the rate-dependent mechanical response of structures under earthquake excitation. However, time delay in RTHS can cause inaccurate results and experimental instabilities. Thus, this study proposes a model-based adaptive control strategy using a Kalman filter (KF) to minimize the time delay and improve RTHS stability and accuracy. In this method, the adaptive control strategy consists of three parts-a feedforward controller based on the discrete inverse model of a servohydraulic actuator and physical specimen, a parameter estimator using the KF, and a feedback controller. The KF with the feedforward controller can significantly reduce the variable time delay due to its fast convergence and high sensitivity to the error between the desired displacement and the measured one. The feedback control can remedy the residual time delay and minimize the method's dependence on the inverse model, thereby improving the robustness of the proposed control method. The tracking performance and parametric studies are conducted using the benchmark problem in RTHS. The results reveal that better tracking performance can be obtained, and the KF's initial settings have limited influence on the proposed strategy. Virtual RTHSs are conducted with linear and nonlinear physical substructures, respectively, and the results indicate brilliant tracking performance and superb robustness of the proposed method.

Keywords

Acknowledgement

The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China [grant numbers 51908231 and 51978213], the Fundamental Research Funds for the Central Universities of Huaqiao University [grant number ZQN-912], Natural Science Foundation of Fujian Province [grant number 2020J01058], and the scientific research fund of Huaqiao University [grant number 18BS306].

References

  1. Blakeborough, A., Williams, M.S., Darby, A.P. and Williams, D.M. (2001), "The development of real-time substructure testing", Philosophical Transactions of the Royal Society of London. Series A: Mathe. Phys. Eng. Sci., 359(1786), 1869-1891. https://doi.org/10.1098/rsta.2001.0877
  2. Chen, P.C. and Chen, P.C. (2020), "Robust stability analysis of real-time hybrid simulation considering system uncertainty and delay compensation", Smart Struct. Syst., Int. J., 25(6), 719-732. https://doi.org/10.12989/sss.2020.25.6.719
  3. Carrion, J. and Spencer Jr., B.F. (2007), Model-based Strategies for Real-time Hybrid Testing, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA.
  4. Carrion, J. and Spencer Jr., B.F. (2008), "Real-time hybrid testing using model-based delay compensation", Smart Struct. Syst., Int. J., 4(6), 809-828. https://doi.org/10.12989/sss.2008.4.6.809
  5. Chae, Y., Kazemibidokhti, K. and Ricles, J.M. (2013), "Adaptive time series compensator for delay compensation of servohydraulic actuator systems for real-time hybrid simulation", Earthq. Eng. Struct. Dyn., 42(11), 1697-1715. https://doi.org/10.1002/eqe.2294
  6. Chen, C. and Ricles, J.M. (2009), "Improving the inverse compensation method for real-time hybrid simulation through a dual compensation scheme", Earthq. Eng. Struct. Dyn., 38(10), 1237-1255. https://doi.org/10.1002/eqe.904
  7. Chen, C. and Ricles, J.M. (2010), "Tracking error-based servohydraulic actuator adaptive compensation for real-time hybrid simulation", J. Struct. Eng., 136(4), 432-440. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000124
  8. Chen, C., Ricles, J.M. and Guo, T. (2012), "Improved Adaptive Inverse Compensation Technique for Real-Time Hybrid Simulation", J. Eng. Mech., 138(12), 1432-1446. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000450
  9. Chen, P., Chang, C., Spencer Jr., B.F. and Tsai, K. (2015), "Adaptive model-based tracking control for real-time hybrid simulation", Bull. Earthq. Eng., 13(6), 1633-1653. https://doi.org/10.1007/s10518-014-9681-2
  10. Chen, C., Yang, Y., Hou, H., Peng, C. and Xu, W. (2022), "Real-time hybrid simulation with multi-fidelity Co-Kriging for global response prediction under structural uncertainties", Earthq. Eng. Struct. Dyn., 51(11), 2591-2609. https://doi.org/10.1002/eqe.3690
  11. Darby, A.P., Williams, M.S. and Blakeborough, A. (2002), "Stability and delay compensation for real-time substructure testing", J. Eng. Mech., 128(12), 1276-1284. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:12(1276)
  12. Drazin, P L. and Govindjee, S. (2017), "Hybrid simulation theory for a classical nonlinear dynamical system", J. Sound Vib., 392, 240-259. https://doi.org/10.1016/j.jsv.2016.12.034
  13. Galmez, C. and Fermandois, G. (2022), "Robust adaptive model-based compensator for the real-time hybrid simulation benchmark", Struct. Control Health Monitor., 29(7). https://doi.org/10.1002/stc.2962
  14. Gao, X.Y., Castaneda, N. and Dyke, S.J. (2013), "Real time hybrid simulation: from dynamic system, motion control to experimental error", Earthq. Eng. Struct. Dyn., 42(6), 815-832. https://doi.org/10.1002/eqe.2246
  15. Hakuno, M., Shidawara, M. and Hara, T. (1969), "Dynamic destructive test of a cantilever beam, controlled by an analog-computer", Proceedings of the Japan Society of Civil Engineers, 1969(171), 1-9. https://doi.org/10.2208/jscej1969.1969.171_1
  16. Horiuchi, T. and Konno, T. (2001), "A new method for compensating actuator delay in real-time hybrid experiments", Philosophical Transactions of the Royal Society of London. Series A: Math. Phys. Eng. Sci., 359(1786), 1893-1909. https://doi.org/10.1098/rsta.2001.0878
  17. Horiuchi, T., Inoue, M., Konno, T. and Namita, Y. (1999), "Real-time hybrid experimental system with actuator delay compensation and its application to a piping system with energy absorber", Earthq. Eng. Struct. Dyn., 10(28), 1121-1141. https://doi.org/10.1002/(SICI)1096-9845(199910)28:10<1121::AID-EQE858>3.0.CO;2-O
  18. Huang, L., Chen, C., Guo, T. and Chen, M.H. (2019), "Stability analysis of real-time hybrid simulation for time-varying actuator delay using the Lyapunov-Krasovskii functional approach", J. Eng. Mech., 145(1). https://doi.org/10.1061/(ASCE)EM.1943-7889.0001550
  19. Li, H., Maghareh, A., Montoya, H., Uribe, J.W.C., Dyke, S.J. and Xu, Z. (2021), "Sliding mode control design for the benchmark problem in real-time hybrid simulation", Mech. Syst. Signal Process., 151, 107364. https://doi.org/10.1016/j.ymssp.2020.107364
  20. Li, H., Maghareh, A., Wilfredo Condori Uribe, J., Montoya, H., Dyke, S.J. and Xu, Z. (2022), "An adaptive sliding mode control system and its application to real-time hybrid simulation", Struct. Control Health Monitor., 29(1), e2851. https://doi.org/10.1002/stc.2851
  21. Marsico, M.R. (2014), "Effects of interface delay in real-time dynamic substructuring tests on a cable for cable-stayed bridge", Smart Struct. Syst., Int. J., 14(6), 1173-1196. https://doi.org/10.12989/sss.2014.14.6.1173
  22. Nakashima, M. (2020), "Hybrid simulation: An early history", Earthq. Eng. Struct. Dyn., 49(10), 949-962. https://doi.org/10.1002/eqe.3274
  23. Nakashima, M., Kato, H. and Takaoka, E. (1992), "Development of real-time pseudo dynamic testing", Earthq. Eng. Struct. Dyn., 21(1), 79-92. https://doi.org/10.1002/eqe.4290210106
  24. Najafi, A. and Spencer Jr., B.F. (2019), "Adaptive model reference control method for real-time hybrid simulation", Mech. Syst. Signal Process., 132, 183-193. https://doi.org/10.1016/j.ymssp.2019.06.023
  25. Najafi, A. and Spencer Jr., B.F. (2021), "Multiaxial Real-Time Hybrid Simulation for Substructuring with Multiple Boundary Points", J. Struct. Eng., 147(11), 05021007. https://doi.org/10.1061/(ASCE)ST.1943-541X.0003138
  26. Ning, X., Wang, Z., Zhou, H., Wu, B., Ding, Y. and Xu, B. (2019), "Robust actuator dynamics compensation method for real-time hybrid simulation", Mech. Syst. Signal Process., 131, 49-70. https://doi.org/10.1016/j.ymssp.2019.05.038
  27. Ning, X., Wang, Z. and Wu, B. (2020), "Kalman filter-based adaptive delay compensation for benchmark problem in real-time hybrid simulation", Appl. Sci., 10(20), 7101. https://doi.org/10.3390/app10207101
  28. Ning, X., Wang, Z., Wang, C. and Wu, B. (2022), "Adaptive feedforward and feedback compensation method for real-time hybrid simulation based on a discrete physical testing system model", J. Earthq. Eng., 26(8), 3841-3863. https://doi.org/10.1080/13632469.2020.1823912
  29. Ou, G., Dyke, S.J. and Prakash, A. (2017), "Real time hybrid simulation with online model updating: An analysis of accuracy", Mech. Syst. Signal Process., 84, 223-240. https://doi.org/10.1016/j.ymssp.2016.06.015
  30. Ouyang, Y., Shi, W., Shan, J. and Spencer Jr., B.F. (2019), "Backstepping adaptive control for real-time hybrid simulation including servo-hydraulic dynamics", Mech. Syst. Signal Process., 130, 732-754. https://doi.org/10.1016/j.ymssp.2019.05.042
  31. Peiris, L.D.H., du Bois, J.L. and Plummer, A.R. (2021), "Passivity-based adaptive delay compensation for real-time hybrid tests", Proceedings of the Institution of Mechanical Engineers, Part I: J. Syst. Control Eng., 235(3), 427-432. https://doi.org/10.1177/0959651820945515
  32. Phillips, B.M. and Spencer Jr., B.F. (2013), "Model-based feedforward-feedback actuator control for real-time hybrid simulation", J. Struct. Eng., 139(7), 1205-1214. https://doi.org/10.1177/0959651820945515
  33. Qian, Y., Ou, G., Maghareh, A. and Dyke, S.J. (2014), "Parametric identification of a servo-hydraulic actuator for real-time hybrid simulation", Mech. Syst. Signal Process., 48(1-2), 260-273. https://doi.org/10.1016/j.ymssp.2014.03.001
  34. Shao, X. and Reinhorn, A.M. (2012), "Development of a controller platform for force-based real-time hybrid simulation", J. Earthq. Eng., 16(2), 274-295. https://doi.org/10.1080/13632469.2011.597487
  35. Shi, P., Wu, B., Spencer Jr., B.F., Phillips, B.M. and Chang, C.M. (2016), "Real-time hybrid testing with equivalent force control method incorporating Kalman filter", Struct. Control Health Monitor., 23(4), 735-748. https://doi.org/10.1002/stc.1808
  36. Silva, C.E., Gomez, D., Maghareh, A., Dyke, S.J. and Spencer Jr., B.F. (2020), "Benchmark control problem for real-time hybrid simulation", Mech. Syst. Signal Process., 135, 106381. https://doi.org/10.1016/j.ymssp.2019.106381
  37. Tao, J. and Mercan, O. (2019), "A study on a benchmark control problem for real-time hybrid simulation with a tracking error-based adaptive compensator combined with a supplementary proportional-integral-derivative controller", Mech. Syst. Signal Process., 134, 106346. https://doi.org/10.1016/j.ymssp.2019.106346
  38. Wallace, M.I., Sieber, J., Neild, S.A., Wagg, D.J. and Krauskopf, B. (2005), "Stability analysis of real-time dynamic substructuring using delay differential equation models", Earthq. Eng. Struct. Dyn., 34(15), 1817-1832. https://doi.org/10.1002/eqe.513
  39. Wang, Z., Wu, B., Bursi, O.S., Xu, G. and Ding, Y. (2014), "An effective online delay estimation method based on a simplified physical system model for real-time hybrid simulation", Smart Struct. Syst., Int. J., 14(6), 1247-1267. https://doi.org/10.12989/.2014.14.6.1247
  40. Wang, Z., Ning, X., Xu, G., Zhou, H. and Wu, B. (2019), "High performance compensation using an adaptive strategy for real-time hybrid simulation", Mech. Syst. Signal Process., 133, 106262. https://doi.org/10.1016/j.ymssp.2019.106262
  41. Wang, Z., Xu, G., Li, Q. and Wu, B. (2020), "An adaptive delay compensation method based on a discrete system model for real-time hybrid simulation", Smart Struct. Syst., Int. J., 25(5), 569-580. https://doi.org/10.12989/sss.2020.25.5.569
  42. Xu, D., Zhou, H., Shao, X. and Wang, T. (2019), "Performance study of sliding mode controller with improved adaptive polynomial-based forward prediction", Mech. Syst. Signal Process., 133, 106263. https://doi.org/10.1016/j.ymssp.2019.106263
  43. Zhao, J., French, C., Shield, C. and Posbergh, T. (2003), "Considerations for the development of real-time dynamic testing using servo-hydraulic actuation", Earthq. Eng. Struct. Dyn., 32(11), 1773-1794. https://doi.org/10.1002/eqe.301
  44. Zhou, Z. and Li, N. (2021), "Improving model-based compensation method for real-time hybrid simulation considering error of identified model", J. Vib. Control, 27(21-22), 2523-2535. https://doi.org/10.1177/1077546320961622
  45. Zhou, H., Xu, D., Shao, X., Ning, X. and Wang, T. (2019), "A robust linear-quadratic-gaussian controller for the real-time hybrid simulation on a benchmark problem", Mech. Syst. Signal Process., 133, 106260. https://doi.org/10.1016/j.ymssp.2019.106260