Experimental and analytical studies on stochastic seismic response control of structures with MR dampers

The magneto-rheological (MR) damper contributes to the new technology of structural vibration control. Its developments and applications have been paid significant attentions in earthquake engineering in recent years. Due to the shortages, however, inherent in deterministic control schemes where only several observed seismic accelerations are used as the trivial input and in classical stochastic optimal control theory with assumption of white noise process, the derived control policy cannot effectively accommodate the performance of randomly base-excited engineering structures. In this paper, the experimental and analytical studies on stochastic seismic response control of structures with specifically designed MR dampers are carried out. The random ground motion, as the base excitation posing upon the shaking table and the design load used for structural control system, is represented by the physically based stochastic ground motion model. Stochastic response analysis and reliability assessment of the tested structure are performed using the probability density evolution method and the theory of extreme value distribution. It is shown that the seismic response of the controlled structure with MR dampers gain a significant reduction compared with that of the uncontrolled structure, and the structural reliability is obviously strengthened as well.

[1]  Jan Ming Ko,et al.  Damping identification of MR-damped bridge cables from in-situ monitoring under wind-rain-excited conditions , 2002, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[2]  Jianbing Chen,et al.  The extreme value distribution and dynamic reliability analysis of nonlinear structures with uncertain parameters , 2007 .

[3]  Chin-Hsiung Loh,et al.  Neuro-fuzzy model of hybrid semi-active base isolation system with FPS bearings and an MR damper , 2006 .

[4]  Hyung-Jo Jung,et al.  Vibration mitigation of highway isolated bridge using MR damper-based smart passive control system employing an electromagnetic induction part , 2009 .

[5]  D. Dowrick.  Earthquake risk reduction , 2003 .

[6]  Hyung-Jo Jung,et al.  An Experimental Study of Semiactive Modal Neuro-control Scheme Using MR Damper for Building Structure , 2008 .

[7]  Jianbing Chen,et al.  Stochastic Dynamics of Structures , 2009 .

[8]  T. T. Soong,et al.  An Optimal Nonlinear Feedback Control Strategy for Randomly Excited Structural Systems , 2001 .

[9]  Yongbo Peng,et al.  A physical approach to structural stochastic optimal controls , 2010 .

[10]  James T. P. Yao,et al.  CONCEPT OF STRUCTURAL CONTROL , 1972 .

[11]  Mahmood Hosseini,et al.  Telescopic columns as a new base isolation system for vibration control of high-rise buildings , 2012 .

[12]  Jianbing Chen,et al.  The principle of preservation of probability and the generalized density evolution equation , 2008 .

[13]  Shirley J. Dyke,et al.  Benchmark problems in structural control : Part II : Active tendon system , 1998 .

[14]  Henry T. Y. Yang,et al.  MULTIPLE OBJECTIVE LQG CONTROL OF WIND-ExCITED BUILDINGS , 1997 .

[15]  Shirley J. Dyke,et al.  Benchmark problems in structural control: part I—Active Mass Driver system , 1998 .

[16]  Ding Wang,et al.  Physical random function model of ground motions for engineering purposes , 2011 .

[17]  Jianbing Chen,et al.  Strategy for selecting representative points via tangent spheres in the probability density evolution method , 2008 .

[18]  Yongbo Peng,et al.  Exceedance probability criterion based stochastic optimal polynomial control of Duffing oscillators , 2011 .

[19]  Chin-Hsiung Loh,et al.  Semi-active control of floor isolation system using MR-damper , 2008, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[20]  S. Nagarajaiah,et al.  Seismic response of sliding isolated bridges with MR dampers , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[21]  Z. G. Ying,et al.  Optimal nonlinear feedback control of quasi-Hamiltonian systems , 1999 .

[22]  Jianling Zhang,et al.  A New Proposed Passive Mega-Sub Controlled Structure and Response Control , 2009 .

[23]  Roger Ghanem,et al.  Generalized optimal control policy for stochastic optimal control of structures , 2013 .

[24]  B. F. Spencer,et al.  STATE OF THE ART OF STRUCTURAL CONTROL , 2003 .

[25]  Jianbing Chen,et al.  The equivalent extreme-value event and evaluation of the structural system reliability , 2007 .

[26]  Yongbo Peng,et al.  Probabilistic criteria of structural stochastic optimal controls , 2011 .

[27]  T. T. Soong,et al.  STRUCTURAL CONTROL: PAST, PRESENT, AND FUTURE , 1997 .

[28]  Hyung-Jo Jung,et al.  State-of-the-art of semiactive control systems using MR fluid dampers in civil engineering applications , 2004 .

[29]  Michael C. Constantinou,et al.  Semi-active control systems for seismic protection of structures: a state-of-the-art review , 1999 .

[30]  Yongbo Peng,et al.  Nonlinear stochastic optimal control strategy of hysteretic structures , 2011 .

[31]  Jan Ming Ko,et al.  Field vibration tests of bridge stay cables incorporated with magnetorheological (MR) dampers , 2002, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[32]  Shirley J. Dyke,et al.  Benchmark Control Problems for Seismically Excited Nonlinear Buildings , 2004 .

[33]  Billie F. Spencer,et al.  Modeling and Control of Magnetorheological Dampers for Seismic Response Reduction , 1996 .

[34]  R. Clough,et al.  Dynamics Of Structures , 1975 .

[35]  Kuo-Chun Chang,et al.  Shaking Table Study on Displacement-Based Design for Seismic Retrofit of Existing Buildings Using Nonlinear Viscous Dampers , 2008 .

[36]  Jann N. Yang,et al.  LQG control of lateral–torsional motion of Nanjing TV transmission tower , 2000 .