• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.30-41
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, It needs a robust performance which can get over the nonlinear characteristics due to hull shape. Second, It needs an accurate performance which has the small overshoot phenomenon and steady state error to avoid colliding with ground surface and obstacles. Third, It needs a continuous control input to reduce the acoustic noise. Finally, It needs an effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose a Intelligence depth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed control scheme has robust and accurate performance by continuous control input and has no speed dependency problem.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.176.2-176
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over nonlinear characteristics. Second, it needs accurate performance which have small overshoot phenomenon and steady state error. Third, it needs continuous control input. Finally, it needs interpolation method which can solve the speed dependency problem of controller parameters. To solve these problems, we propose adepth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.367-375
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over modeling error, parameter variation and disturbance. Second, it needs accurate performance which have small overshoot phenomenon and steady state error to avoid colliding with ground surface or obstacles. Third, it needs continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, it needs interpolation method which can sole the speed dependency problem of controller parameters. To solve these problems, we propose a depth control method using Fuzzy Sliding Mode Controller with feedforward control-plane bias term and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• Journal of the Korean Society of Safety
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• v.14 no.4
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• pp.108-113
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• 1999

This paper presents a study on fuzzy speed and flux controller used in a vector control of a CRPWM(Current Ragulated PWM) induction motor drive. In this paper, an approach for an easier design of the fuzzy controller is presented in order to obtain the desired value for the response time with minimal overshoot and to improve the steady state performance for speed step commands. The fuzzy controller is constructed only upon the knowledge of the motor behaviour and the desired speed response, and provides fast and robust control by reducing the effects of nonlinearities, parameter changes and load disturbance. The results of applying the fuzzy logic controller to an IM drive system are compared with those obtained by application of a conventional PI controller. The fuzzy controller provided a better response than the PI controller.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.892-894
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• 1993

In this paper, a new control for the robust position control of a brushless direct drive(BLDD) motor using fuzzy logic controller(FLC) is presented. The integral-proportional(IP) position with speed FLC is employed to obtain the robust BLDD motor system, which is approximately linearized using the field-orientation method for an AC servo. The speed FLC for a BLDD motor has the two rule tables. One is the coarse rule table for the transient state and another is the fine rule table for the steady state. The overall system is controlled by using the microprossor in IBMPC 486 and the the robustness is also obtained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.330-337
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• 2011

This paper presents a new fuzzy speed controller based on a fuzzy angular acceleration observer to realize a robust speed control of permanent magnet synchronous motors(PMSM). The proposed speed controller needs the information of the angular acceleration, thus the first-order fuzzy acceleration observer is designed. The LMI existence condition is given for the proposed fuzzy speed controller, and the gain matrices of the controller are calculated. It is verified that the augmented control system consisting of the fuzzy speed controller and the fuzzy acceleration observer is mathematically stable. To validate the effectiveness of the proposed acceleration observer-based fuzzy speed controller, the simulation and experimental results are shown under motor parameter variations. It is definitely proven that the proposed control scheme can precisely track the speed of a permanent magnet synchronous motor.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.727-728
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• 2006

This paper is proposed robust control based on the vector controlled induction motor drive with adaptive fuzzy learning control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed estimation of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.2
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• pp.81-87
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• 2016

This paper presents a new approach to control of stable motion of single wheel driving robot system of a pitch that is controlled by an in-wheel motor and a roll that is controlled by a reaction wheel. This robot doesn'thave any actuator for a yaw axis control, which makes the derivation of the dynamics relatively simple. The Lagrange equations was applied to derive the dynamic equations of the one wheel driving robot to implement the dynamic speed control of the mobile robot. To achieve the real time speed control of the unicycle robot, the sliding mode control and optical regulator are utilized to prove the reliability while maintaining the desired speed tracking performance. In the roll controller, the sigmoid-function based robust controller has been adopted to reduce the vibration by the situation function. The optimal controller has been implemented for the pitch control to drive the unicycle robot to follow the desired velocity trajectory in real time using the state variables of pitch angle, angular velocity, angle and angular velocity of the driving wheel. The control performance of the control systems from a single dynamic model has been illustrated by the real experiments.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1271-1278
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• 2010

High-speed traction has voltage source variation because the electric power of tractions is supplied by difference traction power system according to operating section. This paper proposes the robust control maintaining constant output performance against voltage source variation for PWM converters of the high speed traction. The proposed scheme consists of feed-forward compensation for current controller by on-line calculating the rms voltage of voltage source. Total dynamic performance of high speed traction can be improved by the reduction of the output voltage ripple which is resulted from voltage source sag and variation. The superior performance and validity of the proposed scheme is proved through the simulation.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.122-128
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• 1996

In high speed and high precision assembly systems such as a surface mounting device and robotend effector, the contact force control is required. As the operation repeats, the repetitive control is applied to reduce the periodic contact force errors. Since high order unmodelled dynamics are easily excited in contact force control, a Q filter was introduced and its robust stability was analyzed. Simulation and Experimental results show the effectiveness of the algorithm.