• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.893-898
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• 2003

Coulomb friction is an important factor for precise position tracking control systems. The control systems with friction causes the steady state error because of being sensitive to the change of system condition and highly nonlinear characteristics. To overcome these problems, we use an estimation scheme of Coulomb friction to experiment for it's compensating. The estimated factor for Coulomb friction is used as a feed-forward compensator to improve the tracking performance of ball-screw systems. The tracking performance was improved by compensating the estimated friction torque in the feed-forward term. And, the sliding mode control which is derived from the Lyapunov stability theorem is applied for robust stability and reducing chattering. The experimental results show that the sliding mode controller with adaptive friction compensator has a good tracking performance compared with the friction uncompensated controller.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.13-16
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• 2002

In this paper, we newly propose a predictor model which is a method to overcome the time-varying delay in a system and we verify that the predictor model is well suited for the time-delayed system and improves the stability a lot through the experiments. The proposed predict compensator compensates uncertain time delays and minimizes variance of system performance. Therefore it is suitable for the control of uncertain systems and nonlinear systems that are difficult to be modeled. The simulation conditions are set for the cases of various input time delays and simulations are applied for the 2-axis robot arms which are drawing a circle on the plane. Conclusively, the proposed predict compensator represents stable properties regardless of the time delay. As a future research, we suggest to develope a robust control algorithm to compensate the random time delay which occurs in the tole-operated systems.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 전력전자학술대회 논문집
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• pp.285-288
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• 2002

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a deadbeat observer To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller The proposed estimator is combined with a high performance load torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.651-653
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• 1998

This thesis propose the prefilter type control strategies using modified chaotic neural networks #or the trajectory control of robotic manipulator. Since the structure of chaotic neural networks and neurons, chaotic neural networks can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis PUMA robot is designed by CNN. The CNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on- line learning and the performance is excellent. The CNN controller have much better controllability and shorter calculation time compared to the RNN controller. Another advantage of the proposed controller could be attached to conventional robot controller without hardware changes.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권4호
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• pp.184-191
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• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.49-52
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• 2002

This paper presents neural load torque observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• Journal of Power Electronics
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• 제11권3호
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• pp.375-380
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• 2011

A STATic synchronous COMpensator (STATCOM) is a shunt connected voltage source converter (VSC) based FACTS controller using Gate Turn Off (GTO) power semiconductor devices employed for reactive power control. The operation principal is similar to that of a synchronous condenser. A typical application of a STATCOM is voltage regulation at the midpoint of a long transmission line for the enhancement of power transfer capability and/or reactive power control at the load centre. This paper presents the modeling of STATCOM with twenty four pulse three level VSC and Type-1 controller to regulate the reactive current or the bus voltage. The performance is evaluated by transient simulation. It is observed that, the STATCOM shows excellent transient response to step change in the reactive current reference. While the eigenvalue analysis is based on D-Q model, the transient simulation is based on both D-Q and 3 phase models of STATCOM (which considers switching action of VSC).

• 조명전기설비학회논문지
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• 제21권5호
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• pp.82-89
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• 2007

여자제어 시스템의 AVR(Automatic Voltage Regulator) 장치는 발전기의 출력 전압을 일정하게 유지시키기 위하여, 여자기의 전압 또는 전류를 발전기 부하 전류 및 전압 변동에 따라 제어하는 역할을 수행한다. 이러한 AVR 장치의 응답성과 제어 특성은 발전기의 부하 변동 또는 과도 응답 상태에서의 출력 특성을 결정하게 된다. 본 논문에서는 고성능 전동기 제어 시스템에 널리 사용되고 있는 PWM 제어 시스템과 부하 변동에 강인하게 동작할 수 있는 과도 응답 보상기를 적용한 고성능 여자 시스템을 제안한다. 과도 응답 보상기는 발전기의 부하 전류 변동에 따라, 여자기의 제어신호를 PID 제어기의 출력에 더하여 빠른 속응성과 안정성을 가지도록 함으로써, 발전기의 출력 전압을 안정적으로 공급할 수 있도록 제어한다. 제안된 고성능 여자 시스템은 컴퓨터 시뮬레이션과 소형 발전기 시스템에 적용된 실험을 통하여 그 성능을 검증하였다.

• 제어로봇시스템학회논문지
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• 제6권10호
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• pp.871-880
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• 2000

A twin-servo mechanism is used to increase the payload capacity and assembling speed of high precision motion control systems such as semiconductor chip mounters. In this paper, we focus on the modeling of the twin-servo system and propose its network representation. And also, we propose a robust synchronizing motion control algorithm to cancel out the skew motion of the twin-servo system caused by different dynamic characteristics of two driving systems and the vibration generated by high accelerating and decelerating motions. The proposed control algorithm consists of separate feedback motion control algorithms for each driving system and a skew motion compensation algorithm. A robust tracking controller based on internal-loop compensation is proposed as a separate motion controller and its disturbance attenuation property is shown. The skew motion compensation algorithm is also designed to maintain the synchronizing motion during high speed operation, and the stability of the whole closed loop system is proved based on passivity theory. Finally, experimental results are shown to illustrate control performance.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권8호
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• pp.557-564
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• 2000

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system can be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. In addition, the robustness is also obtained without affecting overall system response. This method is realized by a floating-point Digital Signal Processor DS1102 Board (TMS320C31).