• International Journal of Automotive Technology
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• v.8 no.4
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• pp.445-453
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• 2007

This paper presents a robust controller design approach for improving vehicle dynamic roll motion performance and guaranteeing the closed-loop system stability in spite of vehicle parameter variations resulting from aging elements, loading patterns, and driving conditions, etc. The designed controller is linear parameter-varying (LPV) in terms of the time-varying parameters; its control objective is to minimise the $H_{\infty}$ performance from the steering input to the roll angle while satisfying the closed-loop pole placement constraint such that the optimal dynamic roll motion performance is achieved and robust stability is guaranteed. The sufficient conditions for designing such a controller are given as a finite number of linear matrix inequalities (LMIs). Numerical simulation using the three-degree-of-freedom (3-DOF) yaw-roll vehicle model is presented. It shows that the designed controller can effectively improve the vehicle dynamic roll angle response during J-turn or fishhook maneuver when the vehicle's forward velocity and the roll stiffness are varied significantly.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.848-851
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• 2005

This paper proposes a design of IIR notch filter with modified pole placements. The pole angle is derived from quadratic programming to find the appropriate pole position on the unit circle in z-plane in order to achieve the symmetry of the amplitude response. The simulation results are shown when compared with the conventional design technique. Moreover, it uses the TMS320C31 DSP chip for hardware implementation. Finally, the hardware implementation can be applied to removal of ECG baseline wander and elimination of AC power line interference in ECG signal.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.317-325
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• 2003

The vibration, which often occurred in a two inertia motor system, makes it difficult to achieve a quick response of speed and disturbance rejection. This paper provides an autonomous pole assignment technique for three kinds of speed controllers (I-P, I-PD, and State feedback) using GAs(Genetic Algorithms) for a two-inertia motor system. Firstly, the optimal parameters are chosen using GAs in view of reducing overshoot and settling time, then those are used in computing the gains of each controller. Some simulation results verify the effectiveness of the proposed design. The proposed controller is expected to be the autonomous design way for controlling a two-inertia motor system with flexible shaft.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.54-57
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• 1988

In this thesis, after the inverted pendulum being made, its state equation was established with parameters obtained by the state space approach and its position stabilization control was performed with VSS. The switching function of VSS was obtained from pole placement method and as the result of VSS control was compared with that of optimal regulator control, its robustness was clarified in sliding mode. The position and stabilization control of the inverted pendulum Wstem were acomplished with VSS.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.83-87
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• 1999

The purpose of this study is to provide the new method for selection of a close to optimal scalar control of linear time-periodic system. The case of scalar control is considered, the gain matrix being assumed to be at worst periodic with the system period T. The form of gain matrix may have various kinds but must have same period, for example, one of each element being represented by Fourier series. As the optimal gain matrix I consider the matrix ensuring the minimum value of the larger real part of the Poincare exponents of the system. Finally we present a pole placement algorithm to make the given system be stable. It is possible to determine the stability of the given periodic system without get the analytic solution. The application of the method does not require the construction of the Floquet solution. At present state of determination of the gain matrix for this case will be done only by systematic numerical search procedures.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3013-3015
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions, At the same time, the fine tunings of their gain parameters are also troublesome, Thus, in this paper, an Evolving Neural Network ControlleY(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm (RVEGA) was presented for stabilization of an IP system with nonlinearity, This proposed ENNC was described by a simple genetic chromosome. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.421-423
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• 2007

In this paper, The authors apply a state feedback control using an optimal control theory to improve the stability of the control and the dynamic response of the DC-DC converter system with a number of different loads. To execute a this state feedback control, The authors present the pole placement technique using Linear Quadratic Regulator(LQR) to optimally control the system. An integrator can also be included in the open-loop path in order to minimize the steady-state error of the output voltage. To confirm the superiority of the controller, The simulation results are presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.1028-1033
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• 2002

This paper concerns on a non-rotating axis-active magnetic bearing (AMB) system subject to base motion. In such a system, it is desirable to retain the axis within the predetermined air-gap. Motivated from this, an optimal acceleration feedforward control is proposed to reduce the base motion response without deteriorating other feedback control performances. Experimental results demonstrate that the proposed feedforward control reduces the air-gap deviation to 29% that by feedback control alone.

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1240-1247
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• 2001

A robust control design scheme using well-developed SISO techniques is proposed for maglev vehicles that are inherently unstable MIMO systems. The proposed separate control method has basically two control loops: a stabilizing loop by a pole-placement technique, and a performance loop using a novel optimal LQ loop-shaping technique. This paper shows that the coupling terms involved in maglev vehicles with multimagnets should not be neglected but compensated for their stability and performance robustness. The robustness properties of the proposed control system are then evaluated under variations of vehicle masses and air gaps through a computer simulation. This paper also describes the reason why the proposed control technique can be suggested as a tool using only SISO techniques in controlling unstable MIMO systems such as maglev vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.361-361
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• 2000

In the 2-mass system with flexible shaft, a torsional vibration is often generated because of the elastic elements in torque transmission as the newly required speed response which is very close to the primary resonant frequency. This vibration makes it difficult to achieve quick responses of speed and disturbance rejection. In this paper, 2-mass system is designed by using pole placement based on optimal control theory fur fast speed response and torsional vibration elimination and using neural network for disturbance rejection in particular. The simulation results show that the proposed controller based on neural network and full state feedback controller has better performance than 려ll state feedback controller, especially fur disturbance rejection.