Integration of identification and vibration control of time-varying structures subject to unknown seismic ground excitation

Abstract

The synthesis of structural health monitoring and vibration control is important in order to provide facilities for constructing smart structures. In recent years, some techniques have been developed to integrate structural identification and optimal vibration control. However, it is still challenging to integrate the identification and vibration control of time-varying structures subject to unknown earthquake excitation. The main difficulties are that structural dynamic responses collected by a simple harmonic motion system are absolute responses under unknown earthquake ground motion while previous identification approaches for unknown external excitation are not applicable for this situation and the need of an efficient algorithm to accurately track the various scenarios of time-varying structures with inexpensive computation to ensure the real-time performance requested by structural vibration control. In this paper, a novel algorithm is presented, in which structural time-varying parameters are treated as ‘virtual unknown inputs’ to the underlying time-invariant structure, a generalized Kalman filter with unknown inputs is proposed for joint identification of joint structural state, unknown earthquake excitation and ‘virtual unknown inputs’ with only partially measured structural absolute responses, and the identification results are integrated in real-time with the instantaneous optimal control scheme to reach the goal of optimal semi-active control provided by magneto-rheological dampers. Some numerical examples of integrated identification and vibration control of various time-varying structures subject to unknown earthquake excitation are used to demonstrate the performances of the proposed algorithm.

Identification of model‐free hysteretic forces of magnetorheological dampers embedded in buildings under unknown excitations using incomplete structural responses

“…Moreover, when the seismic ground motion to a structure is unknown, the unknown ground acceleration is not presented in the measurement equations 38,39 . In this paper, GKF‐UI recently improved by the authors 42 is utilized to identify structural state and unknown inputs in Equation 18.…”

“…In the second stage, the hysteretic forces of MR dampers are proposed to be considered as “unknown fictitious forces” on the linear structure identified in the first stage. The recent generalized Kalman filter with unknown inputs (GKF‐UI) improved by the authors 42 is developed for the identification of all unknown inputs including the “unknown fictitious forces” originated from the hysteretic forces of MR dampers. It is worth noting that the data fusion‐based measurement equations may include or not include the unknown forces in the above two algorithms.…”

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

“…erefore, the structural characteristics of the intelligent structural system must be measured during extreme excitations in real-time. en, the appropriate control forces must then be applied by the control system to reduce dynamic responses and compensate for possible damage to the structure [62,[75][76][77][78].…”

“…Many existing studies in the broader literature [76,[95][96][97][98][99][100][101] have successfully implemented adaptive control schemes on structures. Some controllers, such as the Simple Adaptive Controller (SAC), recently studied by Soares et al [18,102], can be used to reduce the seismic response of structures under seismic excitations.…”

Seismic motion control of structures using an adaptive optimal model-free controller

“…Then, proper control forces should be applied to the structure by the control unit to decrease the dynamic responses and compensate for the probable damages of the structure. A wide range of control approaches is studied to control the behavior of the civil structures (Chae et al, 2012;Lei et al, 2020;Lezgy-Nazargah et al, 2020;Mamat et al, 2020;Yanik et al, 2014). These control methods can be organized in the classic and modern control areas.…”