ACTIVE VIBRATION CONTROL OF SEISMICALLY EXCITED STRUCTURES BY ATMDS: STABILITY AND PERFORMANCE ROBUSTNESS PERSPECTIVE

This paper demonstrates the trade-off between nominal performance and robustness in intelligent and conventional structural vibration control schemes; and, proposes a systematic treatment of stability robustness and performance robustness against uncertainty due to structural damage. The adopted control strategies include an intelligent genetic fuzzy logic controller (GFLC) and reduced-order observer-based (ROOB) controllers based on pole-placement and linear quadratic regulator (LQR) conventional schemes. These control strategies are applied to a seismically excited truss bridge structure through an active tuned mass damper (ATMD). Response of the bridge-ATMD control system to earthquake excitation records under nominal and uncertain conditions is analyzed via simulation tests. Based on these results, advantages of exploiting heuristic intelligence in seismic vibration control, as well as some complexities arising in realistic conventional control are highlighted. It has been shown that the coupled effect of spill-over (due to reduction and observation) and mismatch between the mathematical model and the actual plant (due to uncertainty and modeling errors) can destabilize the conventional closed-loop system even if each is alone tolerated. Accordingly, the GFLC proves itself to be the dominant design in terms of the compromise between performance and robustness.

[1]  Chunxiang Li,et al.  ACTIVE MULTIPLE TUNED MASS DAMPERS FOR REDUCTION OF UNDESIRABLE OSCILLATIONS OF STRUCTURES UNDER WIND LOADS , 2009 .

[2]  Jerry M. Mendel,et al.  Generating fuzzy rules by learning from examples , 1992, IEEE Trans. Syst. Man Cybern..

[3]  T. K. Datta,et al.  Control of suspension bridge flutter instability using pole-placement technique , 2005 .

[4]  Ananth Ramaswamy,et al.  Multi‐objective optimal design of FLC driven hybrid mass damper for seismically excited structures , 2002 .

[5]  Koji Tanida,et al.  Progress in the application of active vibration control technologies to long‐span bridges in Japan , 2002 .

[6]  R. S. Jangid,et al.  OPTIMUM MULTIPLE TUNED MASS DAMPERS FOR BASE-EXCITED DAMPED MAIN SYSTEM , 2004 .

[7]  Chin-Hsiung Loh,et al.  GA-optimized fuzzy logic control of a large-scale building for seismic loads , 2008 .

[8]  Yeong-Bin Yang,et al.  A wideband MTMD system for reducing the dynamic response of continuous truss bridges to moving train loads , 2004 .

[9]  Hyun-Su Kim,et al.  Design of fuzzy logic controller for smart base isolation system using genetic algorithm , 2006 .

[10]  Yozo Fujino,et al.  Design formulas for tuned mass dampers based on a perturbation technique , 1993 .

[11]  Suzana Moreira Avila,et al.  PARAMETRIC STUDY ON MULTIPLE TUNED MASS DAMPERS USING INTERCONNECTED MASSES , 2008 .

[12]  Fulei Chu,et al.  Design of fuzzy controller for smart structures using genetic algorithms , 2003 .

[13]  Zhikun Hou,et al.  A new approach to suppress spillover instability in structural vibration control , 2004 .

[14]  S. Pourzeynali,et al.  Active control of high rise building structures using fuzzy logic and genetic algorithms , 2007 .

[15]  Richard V. Field,et al.  Probabilistic Stability Robustness of Structural Systems , 1996 .

[16]  F. Kozin,et al.  Vibration control of tall buildings , 1983 .

[17]  K. B. Lim Robust Control of Vibrating Structures , 2002 .

[18]  Kenny C. S Kwok,et al.  Active control of along wind response of tall building using a fuzzy controller , 2001 .

[19]  Anastasios I. Dounis,et al.  Evolutionary fuzzy logic control of base‐isolated structures in response to earthquake activity , 2007 .

[20]  Jann N. Yang,et al.  Reduced-order H∞ and LQR control for wind-excited tall buildings , 1998 .

[21]  M. Balas,et al.  Feedback control of flexible systems , 1978 .