Log in

Active control of highway bridges subject to a variety of earthquake loads

  • Published:
Earthquake Engineering and Engineering Vibration Aims and scope Submit manuscript

Abstract

In this paper, a wavelet-filtered genetic-neuro-fuzzy (WGNF) control system design framework for response control of a highway bridge under various earthquake loads is discussed. The WGNF controller is developed by combining fuzzy logic, discrete wavelet transform, genetic algorithms, and neural networks for use as a control algorithm. To evaluate the performance of the WGNF algorithm, it is tested on a highway bridge equipped with hydraulic actuators. It controls the actuators installed on the abutments of the highway bridge structure. Various earthquakes used as input signals include an artificial earthquake, the El-Centro, Kobe, North Palm Springs, Turkey Bolu, Chi-Chi, and Northridge earthquakes. It is proved that the WGNF control system is effective in mitigating the vibration of the highway bridge under a variety of seismic excitation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agrawal A, Tan P, Nagarajaiah S and Zhang J (2009), “Benchmark Structural Control Problem for a Seismically Excited Highway Bridge-Part I: Phase I Problem Definition,” Structural Control and Health Monitoring, 16: 509–529.

    Article  Google Scholar 

  • Ahlawat AS and Ramaswamy A (2000), “Multiobjective Optimal Design of FLC Driven Hybrid Mass Damper for Seismically Excited Structures,” Earthquake Engineering and Structural Dynamics, 31: 1459–1479.

    Article  Google Scholar 

  • Ahlawat AS and Ramaswamy A (2002), “Multiobjective Optimal FLC Driven Hybrid Mass Damper System for Torsionally Coupled, Seismically Excited Structures,” Earthquake Engineering and Structural Dynamics, 31: 2121–2139.

    Article  Google Scholar 

  • Ahlawat AS and Ramaswamy A (2004), “Multiobjective Optimal Fuzzy Logic Control System for Response Control of Wind-Excited Tall Buildings,” ASCE Journal of Engineering Mechanics, 130: 524–530.

    Article  Google Scholar 

  • Al-Dawod M, Samali B, Naghdy F, Kwok KCS and Naghdy F (2004), “Fuzzy Controller for Seismically Excited Nonlinear Buildings,” ASCE Journal of Engineering Mechanics, 130: 407–415.

    Article  Google Scholar 

  • Alli H and Yakut O (2005), “Fuzzy Sliding-mode Control of Structures,” Engineering Structures, 27: 277–284.

    Article  Google Scholar 

  • Arsava SK, Chong JW and Kim Y (2014), “A Novel Health Monitoring Scheme for Smart Structures,” Journal of Vibration and Control, DOI: 10.1177/1077546314533716.

    Google Scholar 

  • Arsava SK, Kim Y, El-Korchi T and Park HS (2013), “Nonlinear System Identification of Smart Structures under High Impact Loads,” Journal of Smart Materials and Structures, 22: DOI: 10.1088/0964-1726/22/5/055008.

  • Arsava SK and Kim Y (2015), “Modeling of Magnetorheological Dampers under Various Impact Loads,” Shock and Vibration, Vol. 2015, Article ID 905186, 20 pages, DOI: 10.1155/2015/905186.

  • Arsava SK, Nam Y and Kim Y (2015), “Nonlinear System Identification of Smart Reinforced Concrete Structures under High Impact Loads,” Journal of Vibration and Control, DOI: 10.1177/1077546314563966.

    Google Scholar 

  • Battaini M, Casciati F and Faravelli L (1998), “Fuzzy Control of Structural Vibration, An Active Mass System Driven by a Fuzzy Controller,” Earthquake Engineering and Structural Dynamics, 27: 1267–1276.

    Article  Google Scholar 

  • Battaini M, Casciati F and Faravelli L (2004), “Controlling Wind Response through a Fuzzy Controller,” ASCE Journal of Engineering Mechanics, 130: 486–491.

    Article  Google Scholar 

  • Cha YJ and Agrawal AK (2013), “Decentralized Output Feedback Polynomial Control of Seismically Excited Structures Using Genetic Algorithm,” Structural Control and Health Monitoring, 20: 241–258.

    Article  Google Scholar 

  • Cha YJ, Agrawal AK, Kim Y and Raich A (2012), “Multi-objective Genetic Algorithms for Cost-effective Distributions of Actuators and Sensors in Large Structures,” Expert Systems with Applications, 39: 7822–7833.

    Article  Google Scholar 

  • Cha YJ, Kim Y, Raich A and Agrawal AK (2013), “Multi-objective Optimization for Actuator and Sensor Layouts of Actively Controlled 3D Buildings,” Journal of Vibration and Control, 19: 942–960.

    Article  Google Scholar 

  • Chen Y, Yang B, Abraham A and Peng L (2007), “Automatic Design of Hierarchical Takagi-sugeno Type Fuzzy Systems Using Evolutionary Algorithms,” IEEE Transactions on Fuzzy Systems, 15: 385–397.

    Article  Google Scholar 

  • Chong JW, Kim Y and Chon K (2014), “Nonlinear Multiclass Support Vector Machine-based Health Monitoring System for Buildings Employing Magnetorheological Dampers,” Journal of Intelligent Material Systems and Structures, 25: 1456–1468.

    Article  Google Scholar 

  • Du H and Zhang N (2008), “Application of Evolving Takagi-sugeno Fuzzy Model to Nonlinear System Identification,” Applied Soft Computing, 8: 676–686.

    Article  Google Scholar 

  • Faravelli L and Rossi R (2002), “Adaptive Fuzzy Control: Theory versus Implementation,” Journal of Structural Control, 9: 59–73.

    Article  Google Scholar 

  • Faravelli L and Yao T (1996), “Use of Adaptive Networks in Fuzzy Control of Civil Structures,” Microcomputer in Civil Engineering, 12: 67–76.

    Article  Google Scholar 

  • Federal Highway Administration U.S. Department of Transportation and Federal Transit Administration (2008), “Status of the National Highways, Bridges, and Transit: Conditions and Performance,” Report to Congress.

    Google Scholar 

  • Goldberg DE (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, New York.

    Google Scholar 

  • Gurley K and Kareem A (1999) “Applications of Wavelet Transforms in Earthquake, Wind and Ocean Engineering,” Engineering Structures, 21: 149–167.

    Article  Google Scholar 

  • Housner GW, Bergman LA, Caughey TK, Chassiakos AG, Claus RO and Masri SF (1997), “Structural control: Past, Present, and Future,” ASCE Journal of Engineering Mechanics, 123: 897–971.

    Article  Google Scholar 

  • Hung SL, Huang CS, Wen CM and Hsu YC (2003), “Nonparametric Identification of a Building Structure from Experimental Data using Wavelet Neural Network,” Computer-Aided Civil and Infrastructure Engineering, 18: 356–368.

    Article  Google Scholar 

  • Jang JSR (1993), “ANFIS: Adaptive-network-based Fuzzy Inference System,” IEEE Transactions on Systems, Man and Cybernetics, 23: 665–85.

    Article  Google Scholar 

  • Johansen TA (1994), “Fuzzy Model Based Control: Stability, Robustness, and Performance Issues,” IEEE Transactions on Fuzzy Systems, 2: 221–234.

    Article  Google Scholar 

  • Johansen TA and Babuška R (2003), “Multi Objective Identification of Takagi-Sugeno Fuzzy Models,” IEEE Transactions on Fuzzy Systems, 11: 847–860.

    Article  Google Scholar 

  • Kim Y, Bai JW and Albano LD (2014c), “Fragility Estimates of Smart Structures with Sensor Faults,” Journal of Smart Materials and Structures, 22: 125012, DOI: 10.1088/0964-1726/22/12/125012.

    Article  Google Scholar 

  • Kim Y, Chong JW, Chon K and Kim JM (2013a), “Wavelet-based AR-SVM for Health Monitoring of Smart Structures,” Journal of Smart Materials and Structures, 22: 015003, DOI: 10.1088/0964-1726/22/1/015003.

    Article  Google Scholar 

  • Kim Y, Hurlebaus S and Langari R (2010c), “Control of a Seismically Excited Benchmark Building Using Linear Matrix Inequality-based Semiactive Nonlinear Fuzzy Control,” ASCE, Journal of Structural Engineering, 136: 1023–1026.

    Article  Google Scholar 

  • Kim Y, Hurlebaus S and Langari R (2011), “MIMO Fuzzy Identification of Building-MR Damper Systems,” International Journal of Intelligent and Fuzzy Systems, 22: 185–205.

    Google Scholar 

  • Kim Y, Hurlebaus S, Sharifi R and Langari R (2009a), “Nonlinear Identification of MIMO Smart Structures,” ASME Dynamic Systems and Control Conference, Hollywood, California, pp. 33–40.

    Google Scholar 

  • Kim Y, Kim C and Langari R (2010a), “Novel Bioinspired Smart Control for Hazard Mitigation of Civil Structures,” Journal of Smart Materials and Structures, 19: 115009, DOI: 10.1088/0964-1726/19/11/115009.

    Article  Google Scholar 

  • Kim Y, Kim YH and Lee S (2015), “Multivariable Nonlinear Identification of Smart Buildings,” Mechanical Systems and Signal Processing, 62–63: 254–271.

    Article  Google Scholar 

  • Kim Y, Kim KH and Shin BS (2014a), “Fuzzy Model Forecasting of Offshore Bar-shape Profiles under High Waves,” Expert Systems with Applications, 41: 5771–5779.

    Article  Google Scholar 

  • Kim Y, Langari R and Hurlebaus S (2009b), “Semiactive Nonlinear Control of a Building Using a Magnetorheological Damper System,” Mechanical Systems and Signal Processing, 23: 300–315.

    Article  Google Scholar 

  • Kim Y, Langari R and Hurlebaus S (2010b), “Modelbased Multi-input, Multi-output Supervisory Semiactive Nonlinear Fuzzy Controller,” Computer-aided Civil and Infrastructure Engineering, 25: 387–393.

    Article  Google Scholar 

  • Kim Y, Mallick R, Bhowmick S and Chen B (2013b), “Nonlinear System Identification of Large-scale Smart Pavement Systems,” Expert Systems with Applications, 40: 3551–3560.

    Article  Google Scholar 

  • Kim HS and Roschke PN (2006), “Design of Fuzzy Logic Controller for Smart Base Isolation System Using Genetic Algorithm,” Engineering Structures, 28: 84–96.

    Article  Google Scholar 

  • Kim Y, Shin SS and Plummer JD (2014b), “A Waveletbased Autoregressive Fuzzy Model for Forecasting Algal Blooms,” Environmental Modeling & Software, 62: 1–10.

    Article  Google Scholar 

  • Kim SB, Yun CB and Spencer BF (2004), “Vibration Control of Wind-excited Tall Buildings Using Sliding Mode Fuzzy Control,” ASCE Journal of Engineering Mechanics, 130: 505–510.

    Article  Google Scholar 

  • Langari R (1999), “Past, Present and Future of Fuzzy Control: A Case for Application of Fuzzy Logic in Hierarchical Control,” Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society-NAFIPS, New York City, New York, pp. 760–765.

    Google Scholar 

  • Loh CH, Wu LY and Lin PY (2003), “Displacement Control of Isolated Structures with Semi-active Control Devices,” Journal of Structural Control, 10: 77–100.

    Article  Google Scholar 

  • Mitchell R, Kim Y, El-Korchi T and Cha YJ (2012a), “Wavelet-neuro-fuzzy Control of Hybrid Building-active Tuned Mass Damper System under Seismic Excitations,” Journal of Vibration and Control, 19:1881–1894.

    Article  Google Scholar 

  • Mitchell R, Kim Y and El-Korchi T (2012b), “System Identification of Smart Structures Using a Wavelet Neuro-fuzzy Model,” Journal of Smart Materials and Structures, 21: DOI: 10.1088/0964-1726/21/11/115009.

  • Mohammadzadeh S, Kim Y and Ahn J (2015), “PCAbased Neuro-fuzzy Model for System Identification of Smart Structures,” Journal of Smart Structures and Systems, 15: 1139–1158.

    Article  Google Scholar 

  • Ning XL, Tan P, Huang DY and Zhou FL (2009), “Application of Adaptive Fuzzy Sliding Mode Control to a Seismically Excited Highway Bridge,” Journal of Structural Control and Health Monitoring, 16: 639–656.

    Article  Google Scholar 

  • Ozbulut OE and Hurlebaus S (2011), “Optimal Design of Superelastic-friction Base Isolators for Seismic Protection of Highway Bridges against Near-field Earthquakes,” Earthquake Engineering and Structural Dynamics, 40: 273–291.

    Article  Google Scholar 

  • Raich AM and Ghaboussi J (2000), “Evolving Structural Design Solution Using an Implicit Redundant Genetic Algorithm,” Structural Multidisciplinary Optimization, 20: 222–231.

    Article  Google Scholar 

  • Schurter KC and Roschke PN (2001), “Neuro-fuzzy Control of Structures Using Magnetorheological Dampers,” Proceedings of the American Control Conference, Arlington, Virginia, pp. 1097–1102.

    Google Scholar 

  • Soong TT (1990), Active Structural Control: Theory and Practice, Longman Scientific, Essex, UK.

    Google Scholar 

  • Soong TT and Dargush GF (1997), Passive Energy Dissipatio n Systems in Structural Engineering, John Wiley and Sons Ltd, NYC, New York.

    Google Scholar 

  • Soong TT and Reinhorn AM (1993), “An Overview of Active and Hybrid Structural Control R-esearch in the US,” Structural Design of Tall and Special Buildings, 2: 192–209.

    Google Scholar 

  • Spencer BF Jr Christenson RE and Dyke SJ (1999), “Next Generation Benchmark Control Problem for Seismically Excited Buildings,” Proceedings of the Second World Conference on Structural Control, 2, Kyoto, Japan, pp. 1351–1360.

    Google Scholar 

  • Spencer BF Jr and Nagarajaiah S (2003), “State of the Art of Structural Control Source,” ASCE Journal of Engineering Mechanics, 129: 845–856.

    Google Scholar 

  • Subramaniam RS, Reinhorn AM, Riley MA and Nagarajaiah S (1996), “Hybrid Control of Structures Using Fuzzy Logic,” Microcomputers in Civil Engineering, 11: 1–17.

    Article  Google Scholar 

  • Symans M and Kelly SW (1999), “Fuzzy Logic Control of Bridge Structures Using Intelligent Semi-active Seismic Isolation Systems,” Earthquake Engineering & Structural Dynamics, 28: 37–60.

    Article  Google Scholar 

  • Taha MR, Noureldin A, Osman A and El-Sheimy N (2004), “Introduction to the Use of Wavelet Multiresolution Analysis for Intelligent Structural Health Monitoring,” Canadian Journal of Civil Engineering, 31: 719–731.

    Article  Google Scholar 

  • Takagi T and Sugeno M (1985), “Fuzzy Identification of Systems and Its Applications to Modeling and Control,” IEEE Transactions on Systems, Man, and Cybernetics, 15: 116–132.

    Article  Google Scholar 

  • Tani A, Kawamura H and Ryu S (1998), “Intelligent Fuzzy Optimal Control of Building Structures,” Engineering Structures, 20: 184–192.

    Article  Google Scholar 

  • Thuillard Marc (2001), Wavelets in Soft Computing, World Scientific, Singapore.

    Google Scholar 

  • Wang AP and Lee CD (2002), “Fuzzy Sliding Mode Control for a Building Structure Based on Genetic Algorithms,” Earthquake Engineering and Structural Dynamics, 31: 881–895.

    Article  Google Scholar 

  • Yager RR and Filev DP (1993), “Unified Structure and Parameter Identification of Fuzzy Models,” IEEE Transactions on Systems, Man, and Cybernetics, 23: 1198–1205.

    Article  Google Scholar 

  • Yan G and Zhou LL (2006), “Integrated Fuzzy Logic and Genetic Algorithms for Multi-objective Control of Structures Using MR Dampers,” Journal of Sound and Vibration, 296: 368–382.

    Article  Google Scholar 

  • Yang YN and Lin S (2005), “Identification of Parametric Variations of Structures Based on Least Squares Estimation and Adaptive Tracking Technique,” ASCE Journal of Engineering Mechanics, 131: 290–298.

    Article  Google Scholar 

  • Yao JTP (1972), “Concept of structural control,” ASCE Journal of the Structural Division, 98(ST7): 1567–1574.

    Google Scholar 

  • Zadeh LA (1965), Fuzzy Sets. Information and Control, 8: 338–353.

    Article  Google Scholar 

  • Zhou L, Chang CC and Wang LX (2003), “Adaptive Fuzzy Control for Nonlinear Buildingmagnetorheological Damper System,” ASCE Journal of Structural Engineering, 129: 905–913.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yeesock Kim.

Additional information

Supported by: MOF (Ministry of Oceans and Fisheries) and a Grant (12-RTIPB01) from Regional Technology Innovation Program funded by MOLIT (Ministry of Land, Infrastructure and Transport) of Korean government

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mitchell, R., Cha, YJ., Kim, Y. et al. Active control of highway bridges subject to a variety of earthquake loads. Earthq. Eng. Eng. Vib. 14, 253–263 (2015). https://doi.org/10.1007/s11803-015-0021-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11803-015-0021-6

Keywords

Navigation