• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1082-1091
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• 2000

In this paper, the efficient equalization method for OFDM(Orthogonal Frequency Division Multiflexing) System using the QAM(Quadrature Amplitude Modulation) in multipath fading channel is proposed in order to faster and more efficiently equalize the received signals that are sent over real channel. In generally, the one-tap linear equalizers have been used in the frequency-domain as the existing equalization method for OFDM system. In this technique, if characteristics of the channel are changed fast, the one-tap linear equalizers cannot compensate for the distortion due to time variant multipath channels. Therefore, in this paper, we use one-tap non-linear equalizers instead of using one-tap linear equalizers in the frequency-domain, and also use the linear equalizer in the time-domain to compensate the rapid performance reduction at the low SNR(Signal-to-Noise Ratio) that is the disadvantage of the non-linear equalizer. In the frequency-domain, when QAM signals, consisting of in-phase components and quadrature (out-phase) components, are sent over the complex channel, the only in-phase and quadrature components of signals distorted by the multipath fading are changed the same as signals distorted by the noise. So the cross components are canceled in the frequency-domain equalizer. The time-domain equalizer and the adaptive algorithm that has lower-error probability and fast convergence speed are applied to compensate for the error that is caused by canceling the cross components in the frequency-domain equalizer. In the time-domain, To compensate for the performance of frequency-domain equalizer the time-domain equalizes the distorted signals at a frame by using the Gold-code as a training sequence in the receiver after the Gold-codes are inserted into the guard signal in the transmitter. By using the proposed equalization method, we can achieve faster and more efficient equalization method that has the reduced computational complexity and improved performance.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2509-2512
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• 2003

The active magnetic bearing(AMB) has statey-state error of the displacement by the external force. This paper presents a PID controller design using LQR method in the active magnetic bearing to compensate for the displacement by the external force.

• Proceedings of the KIEE Conference
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• 1984.07a
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• pp.119-121
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• 1984

This paper presents an adaptive scheme for regulating the perturbed dynamics in the vicinity of a desired trajectory for robotic manipulators. The scheme directly adjusts the control parameters to compensate destabilizing effects of the unknown, but slowly time varying parameters in the perturbation equation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.152-155
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• 1991

A solution to the problem of robot manipulator tracking of a smoothly moving object is given. It is shown that fuzzy prediction rule, fuzzy control can compensate the adverse effects of noise, time delay, unknown object trajectory, and robot modeling uncertainty. Simulations show that the fuzzy logic control results in acceptable precision,

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.317-318
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• 2008

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.4
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• pp.340-346
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• 2008

An unmanned surveillance robot consists of a machine gun, a laser receiver, a thermal imager, a color CCD camera, and a laser illuminator. It has two axis control systems for elevation and azimuth. Because the current robot system is mounded at a fixed post to take care of surveillance tasks, it is necessary to modify such a surveillance robot to be installed on an UGV (Unmanned Ground Vehicle) system in order to watch blind areas. Thus, it is required to have a stabilization system to compensate the disturbance from the UGV. In this paper, a simulation based design scheme has been adopted to develop a mobile surveillance robot. The 3D CAD geometry model has first been produced by using Pro-Engineer. The required pan and tilt motor capacities have been analyzed using ADAMS inverse dynamics analysis. A target tracking and stabilization control algorithm of the mobile surveillance robot has been developed in order to compensate the motion of the vehicle which will experience the rough terrain. To test the performance of the stabilization control system of the robot, ADAMS/simulink co-simulations has been carried out.

• Journal of the Korean Solar Energy Society
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• v.32 no.spc3
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• pp.255-261
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• 2012

Since PV PCS uses output current sensor for ac output current control, the sensor's sensing value includes unnecessary offset inevitably. If PV inverter is controlled by the included offset value, it's output current will generate DC offset. The DC offset of output current for trans-less PV inverter is fatal to grid, which results in saturating grid side transformer. Usually DSP controller of PV inverter reads several times sensing value during initial operation and, finally, it's average value is used for offset calibration. However, if temperature changes, the offset changes, too. And also, the switch device is not ideal, both each switching element of the voltage drop difference and on & off time delay difference generate DC offset. Thus, to compensate for deadtime and the switch voltage drop, feedback control by output current DC offset should be provided to compensate additional distortion of the output current. The validity of the proposed method is confirmed through PSIM simulation.

• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.113-120
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• 2006

In this paper, a vision-based robust controller for tracking the desired trajectory a robot manipulator is proposed. The trajectory is generated to move the feature point into the desired position which the robot follows to reach to the desired position. To compensate the parametric uncertainties of the robot manipulator which contain in the control input, the robust controller is proposed. In addition, if there are uncertainties in the Jacobian, to compensate it, a vision-based robust controller which has control input is proposed as well in this paper. The stability of the closed-loop system is shown by Lyapunov method. The performance of the proposed method is demonstrated by simulations and experiments on a two degree of freedom 5-link robot manipulators.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1796-1799
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• 1997

This thersis presents precise position control emthods of a 3-PRPS in-parallel manipulator for industrial applications such as assembly of highly integrated semiconductors and microsurgery. Since real-time ontrol is one of the most important issues required for industrial application, the experimental hardware is set up with a VME based DSP controller. In the 3-PRPS parallel mainpulator, structurally existing frictiion at three horizontal links considerably degrades the precise position control. In order to compensate the friction of the horizontal links in the joint space, a disturbance compensation usign disturbance and velocity observers has been proposed and investigated. We analyzed the decision method of eigenvalues of the disturbance observer and the effects of the control resulted form tehsystem model errors. Through a series of simulations and experiments, we see that the methods is capable of compensating variations of the robot parameters such as inertia and damping as well as the joint friction. Experiments show that the disturbance compensation method usign disturbance and velocity observer is very effective to compensate the friction. Compared with conventional PID position control, it decreased position errors ina circular motion by approximately 70%.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1205-1210
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• 2001

This paper describes a methodology using neural network to compensate the nonlinear error of deriving speed for electric differential system included in electric vehicle. An electric differential system which drives each of the left and right wheels of the electric vehicle independently. The electric vehicle driven by induction motor has the nonlinear speed error which depends on a steering angle and speed command. When a vehicle drives along a curved road lane, the speed unblance of inner and outer wheels makes vehicles vibration and speed reduction. To compensate for the speed error, we collected the speed data of the inner wheel and outer wheel in various speed and the steering angle data by using an manufactured electric vehicle and the real system. According to the analysis of the acquisited data, we designed the differential speed control system based on a speed error compensator using neural network.