• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1408-1410
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• 2000

The regulation performances needs high control gain in novel output feedback controller but high control gain is decreased relative stability of the total system. Thus, this paper proposed neural network controller(NNC) for output feedback controller. In this scheme, output feedback controller are guarantee global stability and NNC are controller steady-state error and defined optimal control law. And we demonstrated this scheme by simulations.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1411-1413
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• 2000

Distubance of air-gap sensors by rail irregularities are the serious problem deteriorating the performance in the electromagnetic suspension (EMS) systems. Thus, this paper proposes the output feedback controller with discrete kalman filter for the EMS systems. The discrete kalman filter estimate true state value and output feedback controller guarantee stability. The benefit of this scheme are shown by simulation. Therefore air-gap disturbance are rejected successfully.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1430-1435
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• 2006

This study deals with the problem of balance beam system to stabilize about static and sinusoidal disturbance. wherein the design objectives are to keep the gap deviation from static and sinusoidal disturbance. In this paper propose the 2-Degree of Freedom(DOF) structure and a simple first-order controller which is designed by Characteristic ratio assignment (CRA) method. Matlab simulation result verify stabilization of balance beam system despite of disturbance. Hybrid simulation between digital controller and analog plant is presented by Matlab Simulink.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2120-2122
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• 2001

This paper describes a PID controller for an attraction type magnetic levitation system considering $H^{\infty}$ performance. PID controllers are a kind of fixed structure reduced order controllers. Using change of variables a reduced order control problem can be recast into a static output feedback control problem and can be solved efficiently by LMI(Linear Matrix Inequality) method. In this paper, cone complementarity method is adopted and the simulation shows good results.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.959-961
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• 1996

In this paper, we study the modeling and control of Electro-Magnetic Suspension System with 2 Degree Of Freedom. While the previous researchers considered the control of single rail EMS Systems, we consider the control of two rail EMS Systems. We first derive a simple model to represent the dynamics of EMS System with 2 D.O.F., using the Lagrange's method. The nonlinear equations of motion that we derive are shown to be linearizable by coordinate change and nonlinear static state feedback. The nonlinear static state feedback controller is constructed explicitly.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.345-347
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• 1993

It is known that Feedback linearization has important limitations-the full state has to be measured; no robustness is guaranteed with respect to parameter uncertainty and unmodeled dynamics. In this paper, we construct a nonlinear feedback linearization controller for the system containing uncertain parameters and unknown states, in the case of EMS system with rail vibration. Performance of this controller is demonstrated by computer simulation.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.268-270
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• 1993

The implementation of Nonlinear Feedback Linearization control for Electro-Magnetic Suspension system is presented. The controller using TMS320C31 DSP chip was proposed and the experiments were performed Control law for EMS system using feedback linearization is derived and implemented in the DSP. Some tests were constructed far experimental comparison between feedback linearization and classical state feedback The experimental results demonstrate that the feedback linearization controller shows bettor performance than that of the classical state feedback controller and it is robust with respect to disturbance and parameter variation, though some steady-state errors appear.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.280-283
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• 2000

In this paper, a fault tolerant control problem is considered for a class of nonlinear system formulated in a gain scheduling form with LMI-based H-inf control technique Key benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with actuator and/or sensor failures, and the method is compared with the convensional state-feedback and output-feedback controller. It is clearly observed that the proposed control scheme shows an improved output performance in comparision with convensional methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.10
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• pp.104-110
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• 2015

The disturbance observer (DOB) controller has been widely used in various industrial applications since it is capable of achieving robust stability and disturbance rejection. In this paper, we study the effect of Q-filter on disturbance observer controller for Electro-Magnetic suspension (EMS) systems. We consider three Q-filters and analyze their effects on the robust stability against parameter uncertainties due to mass variation. Moreover, we investigate the influence of sensor noise for three Q-filters. According to our study, robust stability improves as the order of Q-filter decreases. On the other hand, the larger the order of Q-filter, the more the effect of sensor noise can be removed.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1327-1329
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• 2005

This paper presents a gam optimization method using genetic algorithm(GA) for a magnetic levitation(Maglev) controller. GA uses the integral of square error(ISE) as performance index. The plant dynamics are described and modelled by mathematical equations. Also, the system apparatus for the Maglev system are described. Using the derived model, to optimize the feedback gains of conventional state feedback controller(SFC), GA is simulated with SIMULINK model. finally, using the optimized feedback gains, SFC is applied to the Maglev system. From the results, we can see that GA can give a solution for the better control performance for the Maglev system.