• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.57-64
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• 2015

In this paper, a model reference adaptive control (MRAC) scheme is applied for the precise and robust motion control of a pneumatic system with load variation. The reference model for MRAC is designed systematically using linear quadratic Gaussian control with loop transfer recovery (LQG/LTR). The sigmoid function of inverse velocity is used to compensate for the nonlinear friction force between the sliding parts. The experimental results show that MRAC effectively overcame the limit of the PID controller when there was unknown disturbance, including abrupt load variation and model uncertainty in the pneumatic control system.

• Journal of KSNVE
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• v.9 no.1
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• pp.33-41
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• 1999

This paper presents a method of actively controlling the interior noise by a trim panel with hybrid feedforward-feedback control loop. The control technique is designed to minimize the vibration of panel whose motion is limited to that of a piston (out-of-plane motion). The hybrid controller consists of an adaptive feedforward controller in conjunction with a linear quadratic Gaussian (LQG) feedback controller. In order to maintain control performance of both persistent and transient disturbances, the feedback loop speeds up the adaptation rate of feedforward controller by improving damping capacity of secondary plant related with the adaptation rule. Numerical simulation and experimental result indicate that the hybrid controller is a more effective method for reducing the vibration of the panel (and therefore the interior noise) compared to using feedforward controller.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.57-66
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• 1999

In this paper, we propose design methods of suspension controller for magnetically levitated system(MAGLEV). In this interior, the study of Electromagnetic Suspension(EMS) which has several advantages is chiefly achieved but, because the EMS has highly nonlinear and unstable property it is difficult to design the suspension controller maintaining stability and high performance. Here a Gain Scheduling Control(GSC) based on pole-placement scheme and on linear quadratic gaussian(LQG) design is separately presented. The several control performance is shown by simulation.

• Journal of KSNVE
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• v.10 no.6
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• pp.1048-1058
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• 2000

Thipaper presents a methodology to suppress the vibration of thin rectangular plate clamped all edges using piezo-ceramic material as actuators and sensors. Dynamic characteristics of the structure bonded with distributed actuators/sensors are identified by the Multi-Input Multi-Output (MIMO) frequency domain modeling technique based on the experimental data. Hybrid control scheme is adopted and feedback controller is designed by LQG(Linear Quadratic Gaussian). Feedforward controller is adapted by multiple filtered -$x$ LMS(least mean square) algorithm. Experiment result demonstrates the effective reduction of the vibration label for both the transient and persistent external disturbances.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.848-850
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• 1997

A control method of UPFC (Unified Power Flow Controller) to reduce low frequency oscillation is proposed. UPFC is modelled by voltage source, which magnitude and phase angle can be controlled. Because there needs some time to change to desired value, d-axis voltage and Q-axis voltage is modeled by 1st order delay. LQG(Linear Quadratic Gaussian) is used. It is shown that low frequency can be damped by control of UPFC effectively.

• 한국기계연구소 소보
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• s.17
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• pp.157-165
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• 1987

The SWATH concept hull form which is capable of high speed navigation with small oscillatory motions in waves, was developed from the catamaran type hull forms. This paper describes how the motion of a SWATH ship in irregular waves can be reduced by regulating the stabilizing fins. The optimal regulator and LQG (Linear Quadratic Gaussian) controller for vertical plane motion have been applied for both platforming mode and contouring mode controls. The calculations of hydrodynamic coefficients and external forces are possible for defining the system equation for the design purpose of motion control. Performances of the controlled system are compared with those of original system.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.356-360
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• 1990

This paper is an application of Modern control Theory to the control of a current-source inverter (CSI) fed Induction Motor Drive System. A Linear Quadratic-Gaussian (LQG) scheme is developed, in which the Kalman Filter is tuned for high robustness by a method due to Doyle and Stein(8). The design is carried out for a sample system and the robustness by analysis and computer simulation.

• Proceedings of the KSR Conference
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• 2006.11a
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• pp.145-159
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• 2006

This paper describes the development of a clustering based fuzzy controller of an electromagnetic suspension vehicle using gain scheduling method and Kalman filter for a simplified single magnet system. Electromagnetic suspension vehicle systems are highly nonlinear and essentially unstable systems For achieving the levitation control of the DC electromagnetic suspension system, we considered a fuzzy system modeling method based on clustering algorithm which a set of input/output data is collected from the well defined Linear Quadratic Gaussian(LQG) controller. Simulation results show that the proposed clustering based fuzzy controller methodology robustly yields uniform performance with adequate gap response over the mass variation range.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.4 s.44
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• pp.43-54
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• 2005

This paper presents cost-effectiveness evaluation of semi-active control system for cable-stayed bridge under earthquake excitations with various magnitudes and frequency contents. Semi-active control system, which is operated by using Bi-stale control method on the basis of linear quadratic Gaussian (LQG) optimal controller, is designed for the benchmark control problem proposed by Dyke et at. The cost-effectiveness of the proposed control system is defined by the ratio of life-cycle costs between a bridge structure with shock transmission units and a bridge structure with the semi-active control devices. The simulated results show that the damper cost has little influence on the cost-effectiveness of the semi-active control system while the cost-effectiveness is quite sensitive to the damage cost induced by the bridge failure. It is also found that the semi-active control system guarantees relatively high cost-effectiveness for the cable-stayed bridge subject to the ground motions in the regions of moderate seismicity with soft soil condition and strong seismicity with stiff soil condition.

• Smart Structures and Systems
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• v.23 no.1
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• pp.1-14
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• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.