• Smart Structures and Systems
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• v.21 no.4
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• pp.389-395
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• 2018

This paper presents the application of a semi-active fuzzy based control system for seismic response reduction of a single degree-of-freedom (SDOF) framed structure using a Magnetorheological (MR) damper. Semi-active vibration control with MR dampers has been shown to be a viable approach to protect building structures from earthquake excitation. Moreover, intelligent damping systems based on soft-computing techniques such as fuzzy logic models have the inherent robustness to deal with typical uncertainties and non-linearities present in civil engineering structures. Thus, the proposed semi-active control system uses fuzzy logic based models to simulate the behavior of MR damper and also to develop the control algorithm that computes the required control signal to command the actuator. The results of the numerical simulations show the effectiveness of the suggested semi-active control system in reducing the response of the SDOF structure.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.495-502
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• 2006

Seismic performance of semi-active fuzzy control algorithm to operate MR dampers for coupling adjacent building is investigated in this paper. In the proposed semi-active control technique, the fuzzy logic is used as a method to adjust input voltage to MR damper. In order to validate control performance of proposed technique, the seismic performance of the semi-active fuzzy control system is compared with that of passive control system where the input voltage to MR damper is set to display maximum damping force. The simulated results show that the semi-active fuzzy control technique effectively regulates the trade-off existing between seismic responses of two buildings subject to various earthquake excitations.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.69-79
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• 2011

This paper proposes a GA-based optimal fuzzy control technique for the vibration control of earthquakeexcited adjacent structures interconnected with semi-active magneto-rheological(MR) dampers. Rule-based fuzzy logic controllers are designed first by implementing heuristic knowledge and the genetic algorithm(GA) is then introduced to optimally tune the fuzzy controllers for enhancing the seismic performance of semi-active control system. For practical implementation, the fuzzy controller simply uses locally measured responses of the dampers involved and directly returns the input voltage to the magneto-rheological dampers in real time through the fuzzy inference mechanism. The local measurement based fuzzy controller provides optimal damping force in a decentralized manner so that it does not require a primary central controller unlike the conventional semi-active control techniques. As a result, it can avoid the unbridgeable discrepancy between the desired control force and the actual damper force that may occur in the conventional control approaches. The validity and effectiveness of the proposed control method are shown numerically on two 20-story earthquake-excited buildings interconnected with MR dampers.

• International Journal of Safety
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• v.10 no.1
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• pp.22-31
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• 2011

Seismic response control method of the bridge structures with semi-active control device, i.e., magneto-rheological (MR) damper, is studied in this paper. Design of various kinds of clipped optimal controller and fuzzy controller are suggested as a semi-active control algorithm. For determining the control force of MR damper, clipped optimal control method adopts bi-state approach, but the fuzzy control method continuously quantifies input currents through fuzzy inference mechanism to finely modulate the damper force. To investigate the performances of the suggested control techniques, numerical simulations of a multi-span continuous bridge system subjected to various earthquakes are performed, and their performances are compared with each other. From the comparison of results, it is shown that the fuzzy control system can provide well-balanced control force between girder and pier in the view point of structural safety and stability and be quite effective in reducing both girder and pier displacements over the existing control method.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.6 s.46
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• pp.75-90
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• 2005

This paper proposes semi-active fuzzy control technique of magneto-rheological dampers for seismic response control of cable-stayed bridges. Through the fuzzy inference process, the proposed technique performs the semi-active control with the responses of MR dampers only. Moreover, differently from the conventional semi-active control technique, this technique does not require additional active controller for the primary controller, which provides a simple design process. in order to validate the control performance of the proposed technique, the semi-active fuzzy control technique is applied to the benchmark control problem of cable-stayed bridge and its control performance is compared with those of conventional semi-active control techniques. The comparative results show that the proposed fuzzy control technique can be an effective control strategy by efficiently and simultaneously reducing the mutual conflicting responses such as the shear forces and moments at the base of the lowers, longitudinal displacement of the deck, and tensions in the stay cables.

• Smart Structures and Systems
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• v.5 no.3
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• pp.261-277
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• 2009

A fuzzy-sliding mode controller is presented to control the dynamics of semi-active suspension systems of vehicles using magneto-rheological (MR) fluid dampers. A full car model is used to design and evaluate the performance of the proposed semi-active controlled suspension system. Four mixed mode MR dampers are designed, manufactured, and integrated with four independent sliding mode controllers. The siding mode controller is designed to decrease the energy consumption and maintain robustness. In order to overcome the chattering of the sliding mode controllers, a fuzzy logic control strategy is merged into the sliding mode controller. The proposed fuzzy-sliding mode controller is designed and fabricated. The performance of the semi-active suspensions is evaluated in both the time and frequency domains. The obtained results demonstrate that the proposed fuzzy-sliding mode controller can effectively suppress the vibration of vehicles and improve their ride comfort and handling stability. Furthermore, it is shown that the "chattering" of the sliding mode controller is smoothed when it is integrated with a fuzzy logic control strategy. Although the cost function of the fuzzy-sliding mode control is a slightly higher than that of a classical LQR controller, the control effectiveness and robustness are enhanced considerably.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.148-154
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• 2012

Purpose: In order to improve road-friendliness of heavy vehicles, a fuzzy hybrid control strategy consisting of a hybrid control strategy and a fuzzy logic control module is proposed. The performance of the proposed strategy should be effectively evaluated using a hardware-in-the-loop (HIL) simulation model of a semi-active suspension system based on the fuzzy hybrid control strategy prior to real vehicle implementations. Methods: A hardware-in-the-loop (HIL) simulation system was synthesized by utilizing a self-developed electronic control unit (ECU), a PCI-1711 multi-functional data acquisition board as well as the previously developed quarter-car simulation model. Road-friendliness of a semi-active suspension system controlled by the proposed control strategy was simulated via the HIL system using Dynamic Load Coefficient (DLC) and Dynamic Load Stress Factor (DLSF) criteria. Results: Compared to a passive suspension, a semi-active suspension system based on the fuzzy hybrid control strategy reduced the DLC and DLSF values. Conclusions: The proposed control strategy of semi-active suspension systems can be employed to improve road-friendliness of road vehicles.

• Structural Engineering and Mechanics
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• v.36 no.2
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• pp.181-195
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• 2010

Coupled building control is a viable method to protect tall buildings from seismic excitation. In this study, the semi-active control of a building complex is investigated for mitigating seismic responses. The building complex is formed of one main building and one podium structure connected through Magneto-Rheological (MR) Dampers and Tuned Mass Damper. The conventional semi-active control techniques require a primary controller as a reference to determine the desired control force, and modulate the input voltage of the MR damper by comparing the desired control force. The fuzzy logic directly determines the input voltage of an MR damper from the response of the MR damper. The control performance of the proposed fuzzy control technique for the MR damper is evaluated for the control problem of a seismically-excited building complex. In this paper, a building complex that include a 14-story main building and an 8-story podium structure is applied as a numerical example to demonstrate the effectiveness of semi-active control with Magneto-Rheological dampers and its comparison with the passive control with the Tuned Mass Damper and two uncoupled buildings and hybrid semi-active control including the Tuned Mass Damper and Magneto-Rheological dampers while they are subject to the earthquake excitation. The numerical results show that semi-active control and hybrid semi-active control can significantly mitigate the seismic responses of both buildings, such as displacement and shear force responses, and fuzzy control technique can effectively mitigate the seismic response of the building complex.

• Smart Structures and Systems
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• v.12 no.6
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• pp.595-617
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• 2013

Semi-active control equipments are used to effectually enhance the seismic behavior of structures. Magneto-rheological (MR) dampers are semi-active devices that can be utilized to control the response of structures during seismic loads and have received voracious attention for response suppression. They supply the adaptability of active devices and stability and reliability of passive devices. This paper presents an optimal fuzzy logic control scheme for vibration mitigation of buildings using magneto-rheological dampers subjected to near-fault ground motions. Near-fault features including a directivity pulse in the fault-normal direction and a fling step in the fault-parallel direction are considered in the requisite ground motion records. The membership functions and fuzzy rules of fuzzy controller were optimized by genetic algorithm (GA). Numerical study is performed to analyze the influences of near-fault ground motions on a building that is equipped with MR dampers. Considering the uncontrolled system response as the base line, the proposed method is scrutinized by analogy with that of a conventional maximum dissipation energy (MED) controller to accentuate the effectiveness of the fuzzy logic algorithm. Results reveal that the fuzzy logic controllers can efficiently improve the structural responses and MR dampers are quite promising for reducing seismic responses during near-fault earthquakes.

• Smart Structures and Systems
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• v.19 no.4
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• pp.351-360
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• 2017

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.