Earthquakes and Structures

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A novel grey TMD control for structures subjected to earthquakes

  • Z.Y., Chen (School of Science, Guangdong University of Petrochemical Technology) ;
  • Ruei-Yuan, Wang (School of Science, Guangdong University of Petrochemical Technology) ;
  • Yahui, Meng (School of Science, Guangdong University of Petrochemical Technology) ;
  • Timothy, Chen (California Institute of Technology)
  • Received : 2022.04.23
  • Accepted : 2022.12.09
  • Published : 2023.01.25
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Abstract

A model for calculating structure interacted mechanics is proposed. A structural interaction model and controller design based on tuned mass damping (TMD) was developed to control the induced vibration. A key point is to introduce a new analytical model to evaluate the properties of the TMD that recognizes the motion-dependent nonlinear response observed in the simulations. Aiming at the problem of increased current harmonics and low efficiency of permanent magnet synchronous motors for electric vehicles due to dead time effect, a dead time compensation method based on neural network filter and current polarity detection is proposed. Firstly, the DC components and the higher harmonic components of the motor currents are obtained by virtue of what the neural network filters and the extracted harmonic currents are adjusted to the required compensation voltages by virtue of what the neural network filters. Then, the extracted DC components are used for current polarity dead time compensation control to avert the false compensation when currents approach zero. The neural network filter method extracts the required compensation voltages from the speed component and the current polarity detection compensation method obtains the required compensation voltages by discriminating the current polarity. The combination of the two methods can more precisely compensate the dead time effect of the control system to improve the control performance. Furthermore, based on the relaxed method, the intelligent approach of stability criterion can be regulated appropriately and the artificial TMD was found to be effective in reducing cross-wind vibrations.

Keywords

Acknowledgement

The authors are grateful for the research grants given to Ruei Yuan Wang from the Projects of Talents Recruitment of GDUPT, Peoples R China under Grant NO. 2019rc098, and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (NO. 2021rc002) in Guangdong Province, Peoples R China. as well as to the anonymous reviewers for constructive suggestions.

References

  1. Adeli, H. and Jiang, X.M. (2021), "Dynamic fuzzy wavelet neural network model for structural system identification", J. Struct. Eng., 132(1), 102-111. https://doi.org/10.1061/(ASCE)0733-9445(2006)132:1(102). 
  2. Ban, Y., Liu, M., Wu, P., Yang, B., Liu, S., Yin, L. and Zheng, W. (2022), "Depth estimation method for monocular camera defocus images in microscopic scenes", Electr., 11(13), 2012. https://doi.org/10.3390/electronics11132012. 
  3. Bedirhanoglu, I. (2020), "A practical neuro-fuzzy model for estimating modulus of elasticity of concrete", Struct. Eng. Mech., 51(2), 249-265. https://doi.org/10.12989/sem.2014.51.2.249. 
  4. Cao, B., Yan, Y., Wang, Y., Liu, X., Lin, J.C., Sangaiah, A.K. and Lv, Z. (2022), "A multiobjective intelligent decision-making method for multistage placement of PMU in power grid enterprises", IEEE Trans. Industr. Inform., 2022, 1-9. https://doi.org/10.1109/TII.2022.3215787. 
  5. Chan, J., Xu, S. and Zhang, B. (2017), "Single/multiple integral inequalities with applications to stability analysis of time-delay systems", IEEE Trans. Automat. Control, 62(7), 3488-3493. https://doi.org/10.1109/TAC.2016.2617739. 
  6. Chang, M. (2010), "An adaptive self-organizing fuzzy sliding mode controller for a 2-DOF rehabilitation robot actuated by pneumatic muscle actuators", Control Eng. Pract., 18(1), 13-22. https://doi.org/10.1016/j.conengprac.2009.08.005. 
  7. Chen, C.W. (2014), "A criterion of robustness intelligent nonlinear control for multiple time-delay systems based on fuzzy Lyapunov methods", Nonlin. Dyn., 76(1), 23-31. https://doi.org/10.1007/s11071-013-0869-9. 
  8. Chen, T., Huang, Y.C., Hung, C.C., Frias, S., Muhammad, J.A. and Chen, C.Y.J. (2021), "Smart structural stability and NN based intelligent control for nonlinear systems", Smart Struct. Syst., 27(6), 917-926. https://doi.org/10.12989/sss.2021.27.6.917. 
  9. Dang, W., Guo, J., Liu, M., Liu, S., Yang, B., Yin, L. and Zheng, W. (2022), "A semi-supervised extreme learning machine algorithm based on the new weighted kernel for machine smell", Appl. Sci., 12(18), 9213. https://doi.org/10.3390/app12189213. 
  10. Gong, X., Wang, L., Mou, Y., Wang, H., Wei, X., Zheng, W. and Yin, L. (2022), "Improved four-channel PBTDPA control strategy using force feedback bilateral teleoperation system", Int. J. Control, 20(3), 1002-1017. https://doi.org/10.1007/s12555-021-0096-y. 
  11. Hasan, S.D., Islam, N. and Moin, K. (2010), "A review of fixed offshore platforms under earthquake forces", Struct. Eng. Mech., 35(4), 479-491. https://doi.org/10.12989/sem.2010.35.4.479. 
  12. Hsu, W., Yang, R., Chang, F., Wu, H. and Chen, H. (2015), "Experimental study of floating offshore platform in combined wind/wave/current environment", Int. J. Offshore Polar Eng., 26(2), 125-131. https://doi.org/10.17736/ijope.2016.mmr13. 
  13. Hu, Y., Jiang, P., Jiang, H. and Tsai, J. (2021), "Bankruptcy prediction using multivariate grey prediction models", Grey Syst.: Theory Appl., 11(1), 46-62. https://doi.org/10.1108/GS-12-2019-0067. 
  14. Huang, H., Yao, Y., Liang, C. and Ye, Y. (2022), "Experimental study on cyclic performance of steel-hollow core partially encased composite spliced frame beam", Soil Dyn. Earthq. Eng., 163, 107499. https://doi.org/10.1016/j.soildyn.2022.107499. 
  15. Huang, S., Lyu, Y., Sha, H. and Xiu, L. (2021), "Seismic performance assessment of unsaturated soil slope in different groundwater levels", Landslides, 18(8), 2813-2833. https://doi.org/10.1007/s10346-021-01674-w. 
  16. Kordestani, H., Zhang, C., Masri, S.F. and Shadabfar, M. (2021), "An empirical time-domain trend line-based bridge signal decomposing algorithm using Savitzky-Golay filter", Struct. Control Health Monit., 28(7), 2750. https://doi.org/10.1002/stc.2750. 
  17. Li, D., Ge, S.S. and Lee, T.H. (2021), "Fixed-time-synchronized consensus control of multiagent systems", IEEE Trans. Control. Netw. Syst., 8(1), 89-98. https://doi.org/10.1109/TCNS.2020.3034523. 
  18. Li, H.J., Wang, S.Q. and Ji, C.Y. (2002), "Semi-active control of wave-induced vibration for offshore platforms by use of MR damper", China Ocean Eng., 16, 33-40.  https://doi.org/10.3321/j.issn:0890-5487.2002.01.003
  19. Li, J., Chen, M. and Li, Z. (2022), "Improved soil-structure interaction model considering time-lag effect", Comput. Geotech., 148, 104835. https://doi.org/10.1016/j.compgeo.2022.104835. 
  20. Li, J., Zhou, L., Li, S., Lin, G. and Ding, Z. (2023), "Soil-structure interaction analysis of nuclear power plant considering threedimensional surface topographic irregularities based on automatic octree mesh", Eng. Struct., 275, 115161. https://doi.org/10.1016/j.engstruct.2022.115161. 
  21. Lin, C., Yang, Y. and Liu, S. (2020), "A greyness reduction framework for prediction of grey heterogeneous data", Soft Comput., 24(23), 17913-17929. https://doi.org/10.1007/s00500-020-05040-1. 
  22. Liu, X., Tong, D., Huang, J., Zheng, W., Kong, M. and Zhou, G. (2022), "What matters in the e-commerce era? Modelling and mapping shop rents in Guangzhou, China", Land Use Policy, 123, 106430. https://doi.org/10.1016/j.landusepol.2022.106430. 
  23. Lu, S., Guo, J., Liu, S., Yang, B., Liu, M., Yin, L. and Zheng, W. (2022), "An improved algorithm of drift compensation for olfactory sensors", Appl. Sci., 12(19), 9529. https://doi.org/10.3390/app12199529. 
  24. Lu, X., Zhang, J. and Wu, G. (2019), "On translational operator-based DGM(1,1) model and its properties", J. Grey Syst., 31(1), 13-22. 
  25. Ma, H., Tang, G. and Hu, W. (2009), "Feedforward and feedback optimal control with memory for offshore platforms under irregular wave forces", J. Sound Vib., 328(4-5), 369-381. https://doi.org/10.1016/j.jsv.2009.08.025. 
  26. Mao, Y., Zhu, Y., Tang, Z. and Chen, Z. (2022), "A novel airspace planning algorithm for cooperative target localization", Electr., 11(18), 2950. https://doi.org/10.3390/electronics11182950. 
  27. Ni, T., Liu, D., Xu, Q., Huang, Z., Liang, H. and Yan, A. (2020), "Architecture of cobweb-based redundant TSV for clustered faults", IEEE Trans. Very Large Scale Integr. Syst., 28(7), 1736-1739. https://doi.org/10.1109/TVLSI.2020.2995094. 
  28. Patil, K. and Jangid, R.S. (2005), "Passive control of offshore jacket platforms", Ocean Eng., 32(16), 1933-1949. https://doi.org/10.1016/j.oceaneng.2005.01.002. 
  29. Peng, Y. and Dong, M. (2011), "A hybrid approach of HMM and grey model for age-dependent health prediction of engineering assets", Expert Syst. Appl., 38(10), 12946-12953. https://doi.org/10.1016/j.eswa.2011.04.091. 
  30. Procyk, T.J. and Mamdani, E. (1979), "A linguistic self-organizing process controller", Autom., 15(1), 15-30. https://doi.org/10.1016/0005-1098(79)90084-0. 
  31. Quartey-Papafio, T.K., Javed, S.A. and Liu, S. (2021), "Forecasting cocoa production of six major producers through ARIMA and grey models", Grey Syst.: Theory Appl., 11(3), 434-462. https://doi.org/10.1108/GS-04-2020-0050. 
  32. Ren, C., Yu, J., Liu, S., Yao, W., Zhu, Y. and Liu, X. (2022), "A plastic strain-induced damage model of porous rock suitable for different stress paths", Rock Mech. Rock Eng., 55(4), 1887-1906. https://doi.org/10.1007/s00603-022-02775-1. 
  33. Sakthivel, R., Santra, S., Mathiyalagan, K. and Anthoni, S. (2014), "Robust reliable sampled-data control for offshore steel jacket platforms with nonlinear perturbations", Nonlin. Dyn., 78(2), 1109-1123. https://doi.org/10.1007/s11071-014-1500-4. 
  34. Shen, X., Yue, M., Duan, P., Wu, G. and Tan, X. (2019), "Application of grey prediction model to the prediction of medical consumables consumption", Grey Syst. Theory Appl., 9(2), 213-223. https://doi.org/10.1108/GS-11-2018-0059. 
  35. Shi, J., Xiong, P., Yang, Y. and Quan, B. (2021), "Forecasting smog in Beijing using a novel time-lag GM(1,N) model based on interval grey number sequences", Grey Syst. Theory Appl., 11(4), 754-778. https://doi.org/10.1108/GS-02-2020-0025. 
  36. Sie, W.T., Lian, R.J. and Lin, B.F. (2006), "Enhancing grey prediction fuzzy controller for active suspension systems", Veh. Syst. Dyn., 44(5), 407-423. https://doi.org/10.1080/00423110500320425. 
  37. Truong, D. and Ahn, K. (2012), "Wave prediction based on a modified grey model MGM(1,1) for real-time control of wave energy converters in irregular waves", Renew. Energy, 43, 242-255. https://doi.org/10.1016/j.renene.2011.11.047. 
  38. Tsai, P., Pan, J., Liao, B., Tsai, M. and Istanda, V. (2011), "Bat algorithm inspired algorithm for solving numerical optimization problems", Appl. Mech. Mater., 148, 134-137. https://doi.org/10.4028/www.scientific.net/AMM.148-149.134. 
  39. Wang, G., Zhao, B., Lan, R., Liu, D., Wu, B., Li, Y. and Liu, X. (2022a), "Experimental study on failure model of tailing dam overtopping under heavy rainfall", Lithos., 2022(Special 10). https://doi.org/10.2113/2022/5922501. 
  40. Wang, G., Zhao, B., Wu, B., Wang, M., Liu, W., Zhou, H. and Han, Y. (2022b), "Research on the macro-mesoscopic response mechanism of multisphere approximated heteromorphic tailing particles", Lithos., 2022(Special 10), 1977890. https://doi.org/10.2113/2022/19778903. 
  41. Wang, G., Zhao, B., Wu, B., Zhang, C. and Liu, W. (2022c), "Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases", Int. J. Min. Sci. Technol., 2022(7), 1-13. https://doi.org/10.1016/j.ijmst.2022.07.002. 
  42. Wang, H., Wang, Y. and Wu, D. (2021), "A new seasonal cycle GM (1,1) model and its application in railway passenger volume forecasting", Grey Syst.: Theory Appl., 12(2), 293-317. https://doi.org/10.1108/GS-11-2020-0146. 
  43. Wang, S., Yue, Q. and Zhang, D. (2013), "Ice-induced non-structure vibration reduction of jacket platforms with isolation cone system", Ocean Eng., 70, 118-123. https://doi.org/10.1016/j.oceaneng.2013.05.018. 
  44. Yang, J.S. (2022), "Robust mixed 𝐻2⁄𝐻∞ robust active control for offshore steel jacket platform", Nonlin. Dyn., 78, 1503-1514. https://doi.org/10.1007/s11071-014-1531-x. 
  45. Yu, J., Zhu, Y., Yao, W., Liu, X., Ren, C., Cai, Y. and Tang, X. (2021), "Stress relaxation behaviour of marble under cyclic weak disturbance and confining pressures", Meas., 182, 109777. https://doi.org/10.1016/j.measurement.2021.109777. 
  46. Zhang, B.L., Han, Q.L. and Zhang, X.M. (2017), "Recent advances in vibration control of offshore platforms", Nonlin. Dyn., 89(2), 755-771. https://doi.org/10.1007/s11071-017-3503-4. 
  47. Zhang, X.M., Han, Q.L. and Han, D. (2021), "Effects of small time-delays on dynamic output feedback control of offshore steel jacket structures", J. Sound Vib., 330(16), 3883-3900. https://doi.org/10.1016/j.jsv.2011.03.023. 
  48. Zhang, Y., Huang, Y., Zhang, Z., Postolache, O. and Mi, C. (2022a), "A vision-based container position measuring system for ARMG", Meas. Control, 2022, 1-10. https://doi.org/10.1177/00202940221110932. 
  49. Zhang, Y., Luo, J., Li, J., Mao, D., Zhang, Y., Huang, Y. and Yang, J. (2022b), "Fast inverse-scattering reconstruction for airborne high-squint radar imagery based on doppler centroid compensation", IEEE Trans. Geosci. Remote Sens., 60, 1-17. https://doi.org/10.1109/TGRS.2021.3069499. 
  50. Zheng, W., Tian, X., Yang, B., Liu, S., Ding, Y., Tian, J. and Yin, L. (2022a), "A few shot classification methods based on multiscale relational networks", Appl. Sci., 12(8). https://doi.org/10.3390/app12084059. 
  51. Zheng, W., Zhou, Y., Liu, S., Tian, J., Yang, B. and Yin, L. (2022b), "A deep fusion matching network semantic reasoning model", Appl. Sci., 12(7), 3416. https://doi.org/10.3390/app12073416.