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A new framework of multi-objective BELBIC for seismic control of smart base-isolated structures equipped with MR dampers

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Abstract

The main motivation of the present study is to propose a new framework of multi-objective brain emotional learning-based intelligent controller (MOBELBIC) for tuning the command voltage of MR dampers in real-time for smart base-isolated structures. To address the main goal of the seismic control of such structures i.e. creating a suitable trade-off between the conflicting cost functions in terms of the maximum base displacement and superstructure acceleration, a multi-objective particle swarm optimization (MOPSO) algorithm is also utilized. Moreover, a multi-objective proportional–integral–derivative controller (MOPIDC) is proposed for comparison purposes. Then, the validation of both proposed controllers is compared with those given by the passive-off and passive-on statues of the MR damper for a benchmark base-isolated structure subjected to different earthquake excitations. Poor efficacy of the passive-off case is found especially for overcoming the drawbacks of large base displacement during near-field earthquakes. Besides, the passive-on case is significantly able to reduce the maximum and RMS values of the base displacement at the cost of a remarkable increase in the maximum and RMS values of the superstructure inter-story and acceleration, which shows that it cannot meet the main control objectives. The simulation result during different earthquake excitations indicates that the MOBELBIC performs much better than the MOPIDC in the simultaneous reduction of the maximum and RMS of the seismic responses of the studied structure especially in terms of base displacement, inter-story drift, and superstructure acceleration.

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Abbreviations

BELBIC:

Brain emotional learning-based intelligent controller

MOBELBIC:

Multi-objective brain emotional learning-based intelligent controller

MR:

Magneto-Rheological

MOPIDC:

Multi-objective proportional–integral–derivative controller

MOPSO:

Multi-objective particle swarm optimization

PSO:

Particle swarm optimization

PID:

Proportional-integral-derivative

REW:

Reward signal

RMS:

Root mean square

SI:

Sensory inputs

References

  1. Naeim F, Kelly JM (1999) Design of Seismic isolated structures from theory to practice, 2nd edn. Wiley, New York

    Google Scholar 

  2. Narasimhan S, Nagarajaiah S, Johnson EA, Gavin HP (2006) Smart base-isolated benchmark building part I: problem definition. Struct Control Health Monit 13(2–3):573–588

    Google Scholar 

  3. El-Khoury O, Kim C, Shafieezadeh A, Hur JE, Heo GH (2018) Mitigation of the seismic response of multi-span bridges using MR dampers: experimental study of a new SMC-based controller. J Vib Control 24(1):83–99

    Google Scholar 

  4. Katebi J, Shoaei-parchin M, Shariati M, Trung NT, Khorami M (2019) Developed comparative analysis of metaheuristic optimization algorithms for optimal active control of structures. Engineering with Computers, 1–20.

  5. Jarrahi H, Asadi A, Khatibinia M, Etedali S, Samadi A (2020) Simultaneous optimization of placement and parameters of rotational friction dampers for seismic-excited steel moment-resisting frames. Soil Dyn Earthquake Eng 136:106193

    Google Scholar 

  6. Ghelichi M, Goltabar AM, Tavakoli HR, Karamodin A (2020) The cost-effective and multi-objective optimal positioning of active actuators based on tug of war method in seismically excited benchmark highway bridge. Int J Dyn Control 9:557–574

    MATH  Google Scholar 

  7. Xu L, Cui Y, Wang Z (2020) Active tuned mass damper based vibration control for seismic excited adjacent buildings under actuator saturation. Soil Dyn Earthquake Eng 135:106181

    Google Scholar 

  8. Ulusoy S, Nigdeli SM, Bekdaş G (2021) Novel metaheuristic-based tuning of PID controllers for seismic structures and verification of robustness. J Build Eng 33:101647

    Google Scholar 

  9. Lavasani SHH, Doroudi R (2020) Meta heuristic active and semi-active control systems of high-rise building. Int J Struct Eng 10(3):232–253

    Google Scholar 

  10. Bagherkhani A, Baghlani A (2021) Reliability assessment of MR fluid dampers in passive and semi-active seismic control of structures. Prob Eng Mech 63:103114

    Google Scholar 

  11. Zamani AA, Tavakoli S, Etedali S (2017) Fractional order PID control design for semi-active control of smart base-isolated structures: a multi-objective cuckoo search approach. ISA Trans 67:222–232

    Google Scholar 

  12. Etedali S, Zamani AA, Tavakoli S (2018) A GBMO-based PIλDμ controller for vibration mitigation of seismic-excited structures. Autom Constr 87:1–12

    Google Scholar 

  13. Hosseinaei S, Ghasemi MR, Etedali S (2021) Optimal design of passive and active control systems in seismic-excited structures using a new modified TLBO. Periodica Polytechnica Civil Eng 65(1):37–55

    Google Scholar 

  14. Jalali A, Dianati H, Norouzi M, Vatandoost H, Ghatee M (2020) A novel bi-directional shear mode magneto-rheological elastomer vibration isolator. J Intell Mater Syst Struct 31(17):2002–2019

    Google Scholar 

  15. Cruze D, Gladston H, Farsangi EN, Loganathan S, Dharmaraj T, Solomon SM (2020) Development of a multiple coil magneto-rheological smart damper to improve the seismic resilience of building structures. Open Civil Eng J 14(1)

  16. Hormozabad SJ, Soto MG (2021) Load balancing and neural dynamic model to optimize replicator dynamics controllers for vibration reduction of highway bridge structures. Eng Appl Artif Intell 99:104138

    Google Scholar 

  17. Yanik A (2020) Seismic control performance indices for magneto-rheological dampers considering simple soil-structure interaction. Soil Dyn Earthquake Eng 129:105964

    Google Scholar 

  18. Zhou P, Liu M, Kong W, Xu Y, Li H (2021) Modeling and evaluation of magnetorheological dampers with fluid leakage for cable vibration control. J Bridg Eng 26(2):04020119

    Google Scholar 

  19. Dyke SJ, Spencer BF, Sain MK, Carlson JD (1996) Modeling and control of magnetorheological dampers for seismic response reduction. Smart Mater Struct 5(5):565–575

    Google Scholar 

  20. Jansen LM, Dyke SJ (2000) Semiactive control strategies for MR dampers: comparative study. J Eng Mech 126:795–803

    Google Scholar 

  21. Yi F, Dyke SJ, Caicedo JM, Carlson JD (2001) Experimental verification of multi-input seismic control strategies for smart dampers. J Eng Mech 127:1152–1164

    Google Scholar 

  22. Amini F, Mohajeri SA, Javanbakht M (2015) Semi-active control of isolated and damaged structures using online damage detection. Smart Mater Struct. https://doi.org/10.1088/0964-1726/24/10/105002

    Article  Google Scholar 

  23. Zamani AA, Tavakoli S, Etedali S, Sadeghi J (2019) Modeling of a magneto-rheological damper: an improved multi-state-dependent parameter estimation approach. J Intell Mater Syst Struct 30(8):1178–1188

    Google Scholar 

  24. Sherje Nitin P, Deshmukh Sunil V (2020) PID controlled semi-active suspension system using magneto-rheological damper for vehicle. Solid State Technol 63(6):18411–18426

    Google Scholar 

  25. Ma X, Yang S, Shi W (2020) Vibration control and electromagnetic interference analysis of high-speed railway vehicle system with magneto-rheological damper. Int J Appl Electromagn Mech 64:1439–1445

    Google Scholar 

  26. Ji H, Huang Y, Nie S, Yin F, Dai Z (2020) Research on semi-active vibration control of pipeline based on magneto-rheological damper. Appl Sci 10(7):2541

    Google Scholar 

  27. Mai VN, Yoon DS, Choi SB, Kim GW (2020) Explicit model predictive control of semi-active suspension systems with magneto-rheological dampers subject to input constraints. J Intell Mater Syst Struct 31(9):1157–1170

    Google Scholar 

  28. Du X, Han G, Yu M, Peng Y, Xu X, Fu J (2020) Fault detection and fault tolerant control of vehicle semi-active suspension system with magneto-rheological damper. Smart Mater Struct 30(1):014004

    Google Scholar 

  29. Stanikzai MH, Elias S, Matsagar VA, Jain AK (2019) Seismic response control of base-isolated buildings using multiple tuned mass dampers. Struct Design Tall Spl Build 28(3):e1576

    Google Scholar 

  30. Etedali S (2019) Sensitivity analysis on optimal PID controller for nonlinear smart base-isolated structures. Int J Struct Stab Dyn 19(07):1950080

    MathSciNet  Google Scholar 

  31. Fakhrmoosavy SH, Setayeshi S, Sharifi A (2018) A modified brain emotional learning model for earthquake magnitude and fear prediction. Eng Comput 34(2):261–276

    Google Scholar 

  32. Castañeda-Miranda A, Castaño-Meneses VM (2020) Internet of things for smart farming and frost intelligent control in greenhouses. Comput Electron Agric 176:105614

    Google Scholar 

  33. Haghighi MS, Farivar F, Jolfaei A, Tadayon MH (2020) Intelligent robust control for cyber-physical systems of rotary gantry type under denial of service attack. J Supercomput 76(4):3063–3085

    Google Scholar 

  34. Neves TG, de Araújo Neto AP, Sales FA, Vasconcelos LGS, Brito RP (2021) ANN-based intelligent control system for simultaneous feed disturbances rejection and product specification changes in extractive distillation process. Sep Purif Technol 259:118104

    Google Scholar 

  35. Morén J, Balkenius C (2000) A computational model of emotional learning in the amygdala. From Anim Animats 6:115–124

    MATH  Google Scholar 

  36. Jafari M, Xu H (2019) A biologically-inspired distributed fault tolerant flocking control for multi-agent system in presence of uncertain dynamics and unknown disturbance. Eng Appl Artif Intell 79:1–12

    Google Scholar 

  37. Darvish Falehi A (2019) Optimal fractional order BELBIC to ameliorate small signal stability of interconnected hybrid power system. Environ Prog Sustainable Energy 38(5):13208

    Google Scholar 

  38. Sharma P, Kumar V (2019) Design and analysis of a BELBIC controlled semi active suspension system. J Phys Conf Ser 1240(1):012017

    MathSciNet  Google Scholar 

  39. Sharma P, Kumar V (2020) Design and analysis of novel bio inspired BELBIC and PSOBELBIC controlled semi active suspension. Int J Vehicle Perform 6(4):399–424

    Google Scholar 

  40. Khorashadizadeh S, Zadeh SMH, Koohestani MR, Shekofteh S, Erkaya S (2019) Robust model-free control of a class of uncertain nonlinear systems using BELBIC: stability analysis and experimental validation. J Braz Soc Mech Sci Eng 41(8):1–12

    Google Scholar 

  41. Lotfi E, Rezaee AA (2019) Generalized BELBIC. Neural Comput Appl 31(8):4367–4383

    Google Scholar 

  42. Braz César M, Coelho JP, Goncalves J (2019) Semi-active vibration control of a non-collocated civil structure using evolutionary-based BELBIC. Actuators 8(2):43

    Google Scholar 

  43. Braz César M, Paulo Coelho J, Gonçalves J (2018) Evolutionary-based BEL controller applied to a magneto-rheological structural system. Actuators 7(2):29

    Google Scholar 

  44. Johnson EA, Ramallo JC, Spencer BF and Sain MK (1998) Intelligent base isolation systems. In: Proceedings second world conference on structural control, Kyoto, Japan, vol. 1, pp. 367–376. John Wiley & Sons.

  45. Kennedy J (2011) Particle swarm optimization’. Encyclopedia of machine learning. Springer, US, pp 760–766

    Google Scholar 

  46. Coello CAC, Pulido GT, Lechuga MS (2004) Handling multiple objectives with particle swarm optimization. IEEE Trans Evol Comput 8(3):256–279

    Google Scholar 

  47. Shahi M, Sohrabi MR, Etedali S (2018) Seismic control of high-rise buildings equipped with ATMD including soil-structure interaction effects. J Earthquake Tsunami 12(03):1850010

    Google Scholar 

  48. Etedali S, Seifi M, Akbari M (2018) A numerical study on optimal FTMD parameters considering soil-structure interaction effects. Geomech Eng 16(5):527–538

    Google Scholar 

  49. Jamali MR, Arami A, Dehyadegari M, Lucas C, Navabi Z (2009) Emotion on FPGA: model driven approach. Expert Syst Appl 36(4):7369–7378

    Google Scholar 

  50. Lucas C, Shahmirzadi D, Sheikholeslami N (2004) Introducing BELBIC: brain emotional learning based intelligent controller. Intell Autom Soft Comput 10(1):11–21

    Google Scholar 

  51. Beheshti Z, Hashim SZM (2010) A review of emotional learning and it’s utilization in control engineering. Int J Adv Soft Comput Appl 2(2):191–208

    Google Scholar 

  52. Clough RW, Penzien J (2003) Dynamics of structures. McGraw-Hill, New York, Berkeley

    MATH  Google Scholar 

  53. Moayyad P (1983) A study of power spectral density of earthquake accelerograms.

  54. Sues RH, Wen YK, Ang AHS (1985) Stochastic evaluation of seismic structural performance. J Struct Eng 111(6):1204–1218

    Google Scholar 

  55. Hurtado-Gómez JE (2010) Reliability problems in earthquake engineering. Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Barcelona

    Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Shahin Shahr, Isfahan Branch, Technical and Vocational University (TVU), Isfahan, Iran

    Abbas-Ali Zamani

  2. Department of Civil Engineering, Birjand University of Technology, P.O. Box 97175-569, Birjand, Iran

    Sadegh Etedali

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  1. Abbas-Ali Zamani
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  2. Sadegh Etedali
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Correspondence to Abbas-Ali Zamani.

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Zamani, AA., Etedali, S. A new framework of multi-objective BELBIC for seismic control of smart base-isolated structures equipped with MR dampers. Engineering with Computers 38, 3759–3772 (2022). https://doi.org/10.1007/s00366-021-01414-7

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