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Reliability-based robust control for uncertain dynamical systems using feedback of incomplete noi(1).pdf

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Reliability-based robust control for uncertain dynamical systems using feedback of incomplete noi(1).pdf

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Reliability-based robust control for uncertain dynamical systems using feedback of incomplete noi(1).pdf

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文档介绍:EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
Earthquake Engng Struct. Dyn. 2003; 32:751–770 (DOI: )
Reliability-based robust control for uncertain dynamical
systems using feedback of plete noisy
response measurements
Ka-Veng Yuen and James L. Beck∗;†
Division of Engineering and Applied Science; California Institute of Technology; 1201 E. California Blvd;
Pasadena; CA 91125; .
SUMMARY
A reliability-based output feedback control methodology is presented for controlling the dynamic re-
sponse of systems that are represented by linear state-space models. The design criterion is based on
a robust failure probability for the system. This criterion provides robustness for the controlled system
by considering a probability distribution over a set of possible system models with a stochastic model
of the excitation so that robust performance is expected. The mand signal can be calculated
using plete response measurements at previous time steps without requiring state estimation. Ex-
amples of robust structural control using an active mass driver on a shear building model and on a
benchmark structure are presented to illustrate the proposed method. Copyright ? 2003 John Wiley &
Sons, Ltd.
KEY WORDS: benchmark control problem; robust control; robust failure probability; robust reliability;
stochastic control; structural control
1. INTRODUCTION
plete information about a dynamical system and its environment are never avail-
able, the system and excitation cannot be modelled exactly. Classical control design methods
based on a single nominal model of the system may fail to create a control system that pro-
vides satisfactory performance. Robust control methods (. H2, H∞ and -synthesis, etc.)
were therefore proposed so that the optimal controller can provide robust performance and
stability for a set of ‘possible’ models of the system [1; 2]. In a probabilistic robust control
approach, an additional ‘dimension’ is introd

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