• Wind and Structures
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• 제15권3호
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• pp.263-283
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• 2012

This paper presents a framework of nonlinear dynamic analysis of a low-speed moving maglev (magnetically levitated) vehicle subjected to cross winds and controlled using a clipped-LQR actuator with time delay compensation. A four degrees-of-freedom (4-DOFs) maglev-vehicle equipped with an onboard PID (Proportional-Integral-Derivative) controller traveling over guideway girders was developed to regulate the electric current and control voltage. With this maglev-vehicle/guideway model, dynamic interaction analysis of a low-speed maglev vehicle with guideway girders was conducted using an iterative approach. Considering the time-delay issue of unsynchronized tuning forces in control process, a clipped-LQR actuator with time-delay compensation is developed to improve control effectiveness of lateral vibration of the running maglev vehicle in cross winds. Numerical simulations demonstrate that although the lateral response of the maglev vehicle moving in cross winds would be amplified significantly, the present clipped-LQR controller exhibits its control performance in suppressing the lateral vibration of the vehicle.

• 한국군사과학기술학회지
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• 제4권2호
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• pp.179-188
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• 2001

The objective of this paper is to design and implement sliding mode control scheme for an actuation system using BLDC motor. Since the dynamic characteristics of this system with unknown disturbance and parameter variations are very complicated and highly nonlinear, the conventional linear control approaches may not guarantee satisfactory control performances. In order to improve the dynamic performances of this system, a model following sliding mode control(MFSMC) with perturbation estimation approach is designed and implemented. It eliminates the conventional requirements for the knowledge of uncertainty upper boundary. The effectiveness of this control approach is verified by comparison with a PID control through a series of simulation and experimental studies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.428-433
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• 1994

This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

• 유공압시스템학회논문집
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• 제4권4호
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• pp.8-14
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• 2007

The electro-hydraulic pump is usually used in testing equipments which require one control function. But until now, it is not applied to industrial equipments which are exposed to severe working environment and require various control functions. This paper proposes a technique which controls continuously flow, pressure and power by utilizing switching control mode. Mathematical model is developed from the continuity equation for the pressurized control volume and the torque balance for the swash plate motion. To simplify the model we make the linear state equation by differentiating the nonlinear model. We analyze the stability and disturbance by using the state variable model. Finally, we review the control performances of flow, pressure and power by tests using PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.85.4-85
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• 2001

A learning controller is presented for repetitive walking motion of biped robot. The learning control scheme learns the approximate inverse dynamics input of biped walking robot and uses the learned input pattern to generate an input profile of different walking motion from that learnt. In the learning controller, the PID feedback controller takes part in stabilizing the transient response of robot dynamics while the feedforward learning controller plays a role in computing the desired actuator torques for feedforward nonlinear dynamics compensation in steady state. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. The proposed learning control scheme is ...

• 한국기계가공학회지
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• 제3권1호
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• pp.79-83
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• 2004

This study was how to control the mass flow controller in gas supplying system. The flow controller consists of piezoelectric material and sensor with heating wire. It is difficult to obtain accurate model, because MFC was composed of many parts, and the relationship between input and output of controller is nonlinear. The model for control was obtained by time constant and DC gain Based on this model, PID controller was applied to flow controller using DSP board. Also, the results were compared to controller using system identification.

• 한국기계가공학회지
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• 제14권3호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.150-155
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• 1997

In this paper,we present neural network for control of Left Ventricular Assist Device(LVAD)system with a pneumatically driven mock cirulation system. It is necessary to apply high perfomance control techniques, since the LVAD system represent nonlinear and time-varing characteristics. Fortunately, the neural network can be applied to control of a nonliner dynamic system by learning capability. In this study,we identify the LVAD system with neural network and control the LVAD system by PID controller and neural network feedforward controller. The ability and effectiveness of controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation and experiment.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 춘계학술대회 논문집
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• pp.173-177
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• 1992

The Helicopter has a lot of flight modes. The most characteristic flight mode is Hovering. It enables the helicopter to be used in many situations. However, a helicopter has nonlinear dynamics so its mathematical modeling is very difficult. Hence it is not easy to control helicopter in hover. In this paper, RC model helicopter is selected as a plant. To stabilize the behavior of RC model helicopter, Fuzzy alogrithm is used as a controller and one camera is used as a sensor. To get proper Information from camera Image, three characteristic points are attatched to the helicopter and a position recognition algorithm is developed. Experiments are performed to stabilize 3 rotational motions synchronousely with fuzzy control algorithm. As a result, Fuzzy control represents better performances than the conventional PID control.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.1-7
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• 2009

As designing PID control on aircraft, we consider a gain scheduling on altitude and velocity. If pitot tube is not installed in the unpowered air vehicle, the control performance is reduced by the difference between ground speed and air speed with a wind considered. In this paper, a simple guidance controller (LOS: Line of Sight) and the wind estimator using Kalman filter are designed. And we minimize the wind effect through the estimator. Finally, we perform the 6-DOF nonlinear simulation with the wind model to verify the performance of the controller with the wind estimator.