• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.68-75
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• 2007

In this study, the ultimate goal is to acquire stability when turning around efficiently by using the controller which is applied partial feedback linearization of One-wheel Unicycle Robot. When moving around, linear controller could result in unstable factor according to widening operation range. So in order to reduce instability, 1 have developed Non-linear Controller using Partial Feedback Linearization. Compared with linear controller, Non-linear Controller guarantees the superiority of Regulating Control and Tracking Control in direct and also revolution motion of Robot. I'm sure of the Non-linear controller performance through many experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1597-1600
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• 2010

In this paper, a direct controller for nonlinear plants using a neural network is presented. The composed of the control input by using RBF neural networks and auxiliary input to compensate for effects of the approximation errors and disturbances. In the results, using this scheme, the output tracking error between the plant and the reference model can asymptotically converge to zero in the presence of bounded disturbances and approximation errors. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.2
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• pp.152-161
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• 1988

In this paper, a direct method for obtaining the trajectory set points is investigated in discrete-time, which is different from the other conventional schemes. We consider the tracking of a straight line path, where the trajectory set points for manipulator control are determined exactly on the straight line path. For the purpose of the munimum-time operation of manipulators, the problem is formulated as a maximization of the Cartesian distance between two consecutive servo time instants. The maximization is subject to the smoothness and torque constraints. Several algorithms are developed and utilized to maximize the Cartesian distance. The proposed approach has been simulated on a VAX-11/780 computer to verify its performance.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.293-298
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• 1997

The H$_{\infty}$robust controller fur the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of non-convex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. robust design.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.265-270
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• 2001

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of revolute joint robot dynamics. The stability of the robot with the controller is proved by using Lyapunov's direct method. The results of computer simulations also show that the robot system is stable, and has excellent trajectory tracking performance.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.43-48
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• 2014

Two-level inverter has some disadvantages like high harmonics contained in the output current, efficiency limit and stress to switching device as IGBT and FET. Many researches have reported multi-level inverter to complement two-level inverter of problems. In this paper, we suggest MPPT algorithm of multi-string three-level solar inverter that considered nowadays. We added midpoint controller in order to implement the MPPT algorithm because the three-level inverter has to need midpoint controller and procured the stability of direct current link. We verify the superiority of multi-string T-Type inverter and the algorithm we suggested with solar irradiance variation experiment and MPPT efficiency measurement. The MPPT efficiency was confirmed with a high efficiency more than 99.97%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1269-1276
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• 2014

The main objective of this paper is to design DC-DC MPPT circuit using chaotic pulse width modulation to track maximum power from solar PV module for space application. The direct control method of tracking is used to extract maximum power. The nominal duty cycle of the main switch of DC-DC SEPIC converter is adjusted so that the solar panel output impedance is equal to the input resistance of the SEPIC converter which results better spectral performance in the tracked voltages when compared to conventional PWM control. The conversion efficiency of the proposed MPPT system is increased when CPWM is used as a control scheme

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.100-107
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• 2014

This paper presents a co-located and mobile interaction technique using smartphones in a global space. To effectively detect the locations and orientations of smartphones, the proposed approach utilizes Kinect that captures RGB image as well as 3D depth information. Based on the locations and orientations of smartphones, the proposed approach can support direct, collaborative and private interactions with the global space. Thus, it can provide more effective mobile interactions for local space exploration and collaboration.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1705-1714
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• 2018

This paper develops a novel controller called iterative learning sliding mode (ILSM) to control linear and nonlinear fractional-order systems. This control applies a combination structures of continuous and discontinuous controller, conducts the system output to the desired output and achieve better control performance. This controller is designed in the way to be robust against the external disturbance. It also estimates unknown parameters of fractional-order systems. The proposed controller unlike the conventional iterative learning control for fractional systems does not need to apply direct control input to output of the system. It is shown that the controller perform well in partial and complete observable conditions. Simulation results demonstrate very good performance of the iterative learning sliding mode controller for achieving the desired control objective by increasing the number of iterations in the control loop.