Adaptive control for response attenuation of seismically excited cable-stayed bridges
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
Estimation of bridges parameters is bound to give rise to a certain amount of inaccuracy. Given the size of cable-stayed bridge structures, any percentage of error can lead to estimated stiffness, mass, and damping that differ greatly from the actual structural parameters. During their service life, bridge structures experience cracking, temperature variations, localized damage, and deterioration, which result in parametric variation. Adaptive control strategies can be a good alternative to control bridges subjected to seismic excitation, as they present robustness when in face of parametric variation. In this study, a semi-active adaptive control approach is proposed for mitigation of seismic responses of cable-stayed bridges. The approach is based on the simple adaptive control, which is a direct model reference adaptive control strategy for multiple-inputmultiple-output systems, proven to guarantee perfect tracking asymptotically, and successfully avoid the use of observers. The proposed adaptive scheme adopts the nominal bridge controlled by the linearquadratic regulator with full-feedback as a model reference. The adaptive technique is implemented to control semi-active magnetorheological damper devices, considering realistic implementation and design. The schemes ability in reducing seismic response of a cable-stayed bridge subjected to three earthquake records with different angles of incidence is evaluated and its performance is compared to classical control solutions. In order to evaluate robustness of the control scheme proposed, two different parametric changes are introduced. The proposed adaptive scheme gives the least average variation in performance for all the different parametric variations considered. The control solution presents increased robustness when compared to passive and semi-active resettable controllers; it requires a small number of nodes to be monitored and avoids complicated reconstruction of states.
