Seismic control performance indices for magneto-rheological dampers considering simple soil-structure interaction

Yanik, Arcan

doi:10.1016/j.soildyn.2019.105964

Cited by 24 publications

(11 citation statements)

References 25 publications

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“…The MRD became one of the most efficient semi-active structural vibration control devices due to its reported advantages of stability and reversibility. Whenever the structure is subjected to earthquake loads, aside from that, the MRD's high nonlinear dynamic behavior posed a significant obstacle for practical implementation in structural vibration control [51][52][53].…”

Section: Description Of Semi-active Mr Damper (Mrd)-actuation Systemmentioning

confidence: 99%

Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Saeed

Sun

Elias

2022

Journal of Building Engineering

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Section: Description Of Semi-active Mr Damper (Mrd)-actuation Systemmentioning

confidence: 99%

Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Saeed

Sun

Elias

2022

Journal of Building Engineering

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“…The quadratic performance index, represented by eq. ( 13), is minimized in each instant of time, (13) where T is the modal matrix, whose columns are the eigenvectors of A. (14) From the decoupled state equations, the diagonal matrix with the eigenvalues of A is obtained.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Yanik [13] makes a comparison between the LQR controller and the Instantaneous Optimal Controller (IOC) using seismic forcing for a semi-active system applied in a 3storey building and a 5-storey building.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Control Algorithms Applied to an Hybrid Mass Damper Attached to an Wind Turbine Tower

Rocha¹,

Ávila²

2021

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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The structural control, basically, promotes a change in the damping and stiffness properties of the structure, either by the addition of external devices or by the action of external forces. It can be classified as: passive control, active control, hybrid control or semi-active control (Soong & Dargush, 1997). The hybrid mass damper (HMD) is a system that deals with the combination of a tuned mass damper (TMD) with an active control actuator. In addition to requiring lower control forces and maintaining its efficiency over a long range of frequencies, this system has a more robust and reliable control, when compared to active and passive alone (Collette & Chesné, 2016). Among the structures, the wind turbine stands out, which is supported by towers, which due to its geometry and height, are slender, flexible and can suffer excessive levels of vibration caused by the operation of the turbine, as well as by external forces (Woude & Narasimhan, 2014). In this work it is proposed the application of a structural control system, in the way of HMD, to protect a wind tower with theoretical dimensions and with a simplified as single degree of freedom model, submitted to wind and seismic loads that leads to levels of undesirable vibrations that may compromise the safety and integrity of the structure. In addition, it is proposed to compare the performances obtained from the system without control and by the Instantaneous Optimal Control (IOC), Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR) controllers with numerical simulations performed using the MAPLESOFT, MATLAB and its Simulink control toolbox. The results obtained numerically were analyzed and compared with each other, and it was observed that HMD was efficient in reducing the dynamic response of the tower. Although it is a preliminary model, it is a basis for studies in this area to evolve into a more sophisticated model and fullscale applications.

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“…Singh and Moreschi (2002) used a GA to observe and determine the placement of passive control devices in a multistory structure. Yanik (2020) studied the soil–structure interaction effect on response and control efficiency. Abdullah et al (2001) combined gradient-based optimization and GA to obtain the optimal spatial position of actuators in a structure.…”

Section: Introductionmentioning

confidence: 99%

Study on integrated response-based adaptive strategies for control and placement optimization of multiple magneto-rheological dampers-controlled structure under seismic excitations

Wani

Tantray

2021

Journal of Vibration and Control

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The application and optimization of control systems with multiple magneto-rheological dampers integrated into a civil engineering structure is a challenging task. The performance of the control system is strongly linked with the location and arrangement of control devices, and the optimal placement of control devices is inherently linked with the performance objective of the control algorithm. Therefore, for semi-active control devices, the placement algorithm should be well rooted within the control algorithm, for effective structural control. This article proposes response-based adaptive control strategies embedded with the device location optimization algorithm. The acceleration and inter-story drift responses of the structure are considered as the performance objective for two separate control strategies. The flexibility of this approach lies in the fact that the design algorithm for control and location of magneto-rheological dampers can be engineered based on the performance criteria of the system. This study involves numerical simulation of an actual five-story framed structure. The simulation results indicated that the seismic performance of the structure is strongly linked with the number, placement of the magneto-rheological damper, and the performance objective of the control strategy used. Also, the configuration and corresponding control provided by the response-based adaptive strategies performed better than the configuration predicted by the benchmark genetic algorithm using the H2/LQG controller.

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Seismic control performance indices for magneto-rheological dampers considering simple soil-structure interaction

Cited by 24 publications

References 25 publications

Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Comparison of Control Algorithms Applied to an Hybrid Mass Damper Attached to an Wind Turbine Tower

Study on integrated response-based adaptive strategies for control and placement optimization of multiple magneto-rheological dampers-controlled structure under seismic excitations

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