• Smart Structures and Systems
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• v.15 no.4
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• pp.1139-1158
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• 2015

This paper proposes an efficient system identification method for modeling nonlinear behavior of civil structures. This method is developed by integrating three different methodologies: principal component analysis (PCA), artificial neural networks, and fuzzy logic theory, hence named PANFIS (PCA-based adaptive neuro-fuzzy inference system). To evaluate this model, a 3-story building equipped with a magnetorheological (MR) damper subjected to a variety of earthquakes is investigated. To train the input-output function of the PANFIS model, an artificial earthquake is generated that contains a variety of characteristics of recorded earthquakes. The trained model is also validated using the1940 El-Centro, Kobe, Northridge, and Hachinohe earthquakes. The adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. It is demonstrated from the training and validation processes that the proposed PANFIS model is effective in modeling complex behavior of the smart building. It is also shown that the proposed PANFIS produces similar performance with the benchmark ANFIS model with significant reduction of computational loads.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.197-204
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• 2008

The purpose of this paper was to develop a rehabilitation training system which is controlled by electric currents to the Magneto-Rheological dampers system. This system provided the function for the training of the unbalance of the lower extremities. 10 subjects executed the tracing and moving exercises which are presented through the display monitor and confirmed own the capability of performance on the task. The electromyographies of the four muscles in lower extremities were recorded and analyzed in the time and frequency domain the muscles of interest were rectus femoris, biceps femoris, gastrocnemius, tibialis anterior. The experimental results showed that subjects had a task under feedback mode then subjects improve the capability of performance, increasing the in time, decreasing the out time and the distance of body shift. The moving average EMG, spectral energy of four muscle is lower the feedback mode than the constant mode. This could aid the hemiplegic patients to train more easily.

• Smart Structures and Systems
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• v.4 no.6
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• pp.809-828
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• 2008

Real-time hybrid testing is an attractive method to evaluate the response of structures under earthquake loads. The method is a variation of the pseudodynamic testing technique in which the experiment is executed in real time, thus allowing investigation of structural systems with time-dependent components. Real-time hybrid testing is challenging because it requires performance of all calculations, application of displacements, and acquisition of measured forces, within a very small increment of time. Furthermore, unless appropriate compensation for time delays and actuator time lag is implemented, stability problems are likely to occur during the experiment. This paper presents an approach for real-time hybrid testing in which time delay/lag compensation is implemented using model-based response prediction. The efficacy of the proposed strategy is verified by conducting substructure real-time hybrid testing of a steel frame under earthquake loads. For the initial set of experiments, a specimen with linear-elastic behavior is used. Experimental results agree well with the analytical solution and show that the proposed approach and testing system are capable of achieving a time-scale expansion factor of one (i.e., real time). Additionally, the proposed method allows accurate testing of structures with larger frequencies than when using conventional time delay compensation methods, thus extending the capabilities of the real-time hybrid testing technique. The method is then used to test a structure with a rate-dependent energy dissipation device, a magnetorheological damper. Results show good agreement with the predicted responses, demonstrating the effectiveness of the method to test rate-dependent components.

• Journal of Korean Association for Spatial Structures
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• v.21 no.3
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• pp.43-50
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• 2021

A tilted tall building is actively constructed as landmark structures around world to date. Because lateral displacement responses of a tilted tall building occurs even by its self-weight, reduction of seismic responses is very important to ensure structural safety. In this study, a smart tuned mass damper (STMD) was applied to the example tilted tall building and its seismic response control performance was investigated. The STMD was composed of magnetorheological (MR) damper and it was installed on the top floor of the example building. Control performance of the STMD mainly depends on the control algorithn. Fuzzy logic controller (FLC) was selected as a control algorithm for the STMD. Because composing fuzzy rules and tuning membership functions of FLC are difficult task, evolutionary optimization algorithm (EOA) was used to develop the FLC. After numerical simulations, it has been seen that the STMD controlled by the EOA-optimized FLC can effectively reduce seismic responses fo the tilted tall building.

• Smart Structures and Systems
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• v.11 no.5
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• pp.435-451
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• 2013

High-rise buildings are a common feature of urban cities around the world. These flexible structures frequently exhibit large vibration due to strong winds and earthquakes. Structural control has been employed as an effective means to mitigate excessive responses; however, structural control mechanisms that can be used in tall buildings are limited primarily to mass and liquid dampers. An attractive alternative can be found in outrigger damping systems, where the bending deformation of the building is transformed into shear deformation across dampers placed between the outrigger and the perimeter columns. The outrigger system provides additional damping that can reduce structural responses, such as the floor displacements and accelerations. This paper investigates the potential of using smart dampers, specifically magnetorheological (MR) fluid dampers, in the outrigger system. First, a high-rise building is modeled to portray the St. Francis Shangri-La Place in Philippines. The optimal performance of the outrigger damping system for mitigation of seismic responses in terms of damper size and location also is subsequently evaluated. The efficacy of the semi-active damped outrigger system is finally verified through numerical simulation.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.197-208
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• 2017

Among various retrofitting strategies, use of semi-active control for retrofitting a building structure has gained momentum in recent years. One of the techniques for such retrofitting is to connect a weaker building to an adjacent stronger building by semi-active devices, so that performances of a weaker building are significantly improved for seismic forces. In this paper, a ten storey weaker building is connected to an adjacent stronger building using magneto-rheological (MR) dampers, for primarily improving the performance of the weaker building in terms of displacement, drift and base shear. For this, a fuzzy logic controller is specifically developed by fuzzyfying the responses of the coupled system. The performance of the control strategy is compared with the passive-on and passive-off controls. Pounding Mitigation between the two buildings is also investigated using all three control strategies. The results show that there exists a fundamental frequency ratio between the two buildings for which maximum control of the weaker building response takes place with no penalty on the stronger building. There exists also a fundamental frequency ratio where control of the weaker building response is achieved at the expense of the amplification of the stronger building. However, coupling strategy always improves the possibility of pounding mitigation.

• Smart Structures and Systems
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• v.23 no.1
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• pp.91-106
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• 2019

Adopting sloped rolling-type isolation devices underneath a raised floor system has been proved as one of the most effective approaches to mitigate seismic responses of the protected equipment installed above. However, pounding against surrounding walls or other obstructions may occur if such a base-isolated raised floor system is subjected to long-period excitation, leading to adverse effects or even more severe damage. In this study, real-time hybrid simulation (RTHS) is adopted to assess the control performance of a smart base-isolated raised floor system as it is an efficient and cost-effective experimental method. It is composed of multiple sloped rolling-type isolation devices, a rigid steel platen, four magnetorheological (MR) dampers, and protected high-tech equipment. One of the MR dampers is physically tested in the laboratory while the remainders are numerically simulated. In order to consider the effect of input excitation characteristics on the isolation performance, the smart base-isolated raised floor system is assumed to be located at the roof of a building and the ground level. Four control algorithms are designed for the MR dampers including passive-on, switching, modified switching, and fuzzy logic control. Six artificial spectrum-compatible input excitations and three slope angles of the isolation devices are considered in the RTHS. Experimental results demonstrate that the incorporation of semi-active control into a base-isolated raised floor system is effective and feasible in practice for high-tech industry.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.560-564
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• 2007

In order to reduce the level of recoil force, new recoil technology must be employed. The present study discusses a soft-recoil mechanism that can reduce dramatically the recoil force. The dynamics of the soft-recoil system with hydraulic dampers are described and simulated. The results of the simulation show that FOOB system can reduce the recoil force and the recoil stroke compared to conventional systems. However, the FOOB system is not able to perform well when the fault modes happen. Hence, this study uses the MR damper to achieving FOOB under fault modes.

• Smart Structures and Systems
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• v.23 no.6
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• pp.695-702
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• 2019

The number of cable-stayed bridges has been increasing worldwide, causing issues in maintaining the structural safety and integrity of bridges. The stay cable, one of the most critical members in cable-stayed bridges, is vulnerable to wind-induced vibrations owing to its inherent low damping capacity. Thus, vibration mitigation of stay cables has been an important issue both in academia and practice. While a semi-active control scheme shows effective vibration reduction compared to a passive control scheme, real-world applications are quite limited because it requires complicated equipment, including for data acquisition, and power supply. This study aims to develop an Arduino-based integrated cable vibration control system implementing a semi-active control algorithm. The integrated control system is built on the low-cost, low-power Arduino platform, embedding a semi-active control algorithm. A MEMS accelerometer is installed in the platform to conduct a state feedback for the semi-active control. The Linear Quadratic Gaussian control is applied to estimate a cable state and obtain a control gain, and the clipped optimal algorithm is implemented to control the damping device. This study selects the magnetorheological damper as a semi-active damping device, controlled by the proposed control system. The developed integrated system is applied to a laboratory size cable with a series of experimental studies for identifying the effect of the system on cable vibration reduction. The semi-active control embedded in the integrated system is compared with free and passive mode cases and is shown to reduce the vibration of stay-cables effectively.