• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1684-1692
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• 2016

In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1520-1526
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• 1999

This paper presents a current feedback learning controller for dynamic control of DC motors. The proposed controller uses the full third-order dynamics model of DC motor system to drive stable learning rules for virtual current learning input, voltage learning input, and the coefficient of electromotive force. It is shown that the proposed learning controller drives the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one globally asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed adaptive learning controller.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2113-2116
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• 1997

The speed sensorless vector control of induction motor using the rotor speed and flux estimation is widely used. In practice, these schemes depend on the accurate parameters of the machine. If in the vector control scheme an inaccurate parameter of induction motor due to skin effects and to temperature variations is used. it is difficult to achieve correct field orientation. From this reason. we propose robust speed sensorless vector control of induction motor against the variations of parameter and disturbance by using extended Kalman filter. For speed and rotor flux estimation. conventional adaptive flux observer is applied. extended Kalman filter which is correctly capable of estimating rotor flux and load by eliminating virtually influences of structural noises is proposed. Simulation results show the effectiveness of the control strategy proposed here for the induction motor drives.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.571-573
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• 1996

A robust control technique of the PM synchronous motor is presented using an accelerating torque feedback. The accelerating torque is estimated by using an adaptive torque observer and then this estimated torque is controlled by a VSC technique. By employing the proposed torque control, the speed control performance of the motor is improved and the load independency can be realized. The simulations carried out for the PM synchronous motor to verily the effectiveness of the proposed control.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.174-181
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• 1997

A proposed hybrid self-tuning control scheme for single rod hydraulic cylinder which has varying loads is presented here. An adaptive controller is developed for the system that use feedforward and P feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the hybrid self-tuning controller with a constant gain P contro- ller clearly shows its superior ability in handling load changes in quiescent states.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.924-931
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• 2016

In this paper, Various network adaptive MAC scheduling technique is proposed to effectively overcome limits of narrow bandwidth and low transmission speed in underwater. UPFC(Underwater Packet Flow Control) is a technique to reduce both the number of transmission and transmission time using three types (Normal, Blocked, Parallel) of data transmission. In this technique, the load information, in which a transmission node have, is transmitted to destination node using marginal bit in reserved header. Then the transmitted information is referred to determine weighting factor. According to the weighting factor, scheduling is dynamically changed adaptively. The performance of UPFC is analyzed and flow control technique which can be applied to Cluster Based Network and Ad Hoc network as well.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.183-186
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• 2003

In this paper, we proposed fuzzy adaptive resonance theory(ART) combined with principle component analysis(PCA) to recognize and classify indoor environmental gases. In experiment Taguchi gas sensors(TGS) are used to detect VOCs. Using thermal modulation of operating temperature of two sensors, we extract patterns of gases from the voltage across the load resistance. We use the PCA algorithm to reduce dimension so it needs less memory and shortens calculation time. Simulation is accomplished to two directions for fuzzy ART with and without PCA.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1231-1234
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• 1992

In this paper a self-tuning control algorithm has been utilized to control speed of a rolling mill DC drive system. Inner current control loop is composed of predictive current controller and the outer speed control loop is composed of the self-tuning PI or IP controller. Computer simulation results reveal that the adaptive control algorithm using self-tuning control is capable of following the typical set point variations required for a rolling mill in conjunction with load torque variations on the shaft of the drive.