• 한국해양공학회지
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• 제9권2호
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• pp.30-40
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• 1995

In this paper, it is proposed a robust control scheme for real time control of a robot manipulator with parameter uncertainties. The focus of this paper is a new approach of multivariable control schemes for an assembly robot manipulator to achieve the accurate trajectory tracking by joint angles. The proposed control scheme consists of a multivariable feedforward controller and feedback controller. In this control scheme, the feedback controller consists of proportional-derivative type and is designed by the pole placement method. The feedforward controller uses the inverse of the linealized model of robot manipulator dynamics. This feedback controller ensures that each joint enables to track any reference trajectory. The proposed robot controller scheme has a computational efficiency.

• 동력기계공학회지
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• 제19권4호
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• pp.24-29
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• 2015

This paper designs a looper-tension controller for strip top-tail parts in hot strip finishing mills. A three-degree linear model of the looper-tension system is derived by a Taylor's linearization method, where the actuator's dynamics are ignored because of their fast responses. A feedforward shaping controller for the strip top part and a feedforward model reference controller for the strip tail part are respectively designed, they are combined with an ILQ(Inverse Linear Quadratic optimal control) feedback controller for the strip middle part. It is shown from by a computer simulation that the proposed controller is very effective to the strip top-tail parts including the middle part.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• 제어로봇시스템학회논문지
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• 제20권5호
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• pp.543-550
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• 2014

In many industrial processes and operations, such as power plants, petrochemical industries and ships, shell and tube heat exchangers are widely used and probably applicable for a wide range of operating temperatures. The main purpose of a heat exchanger is to transfer heat between two or more medium with temperature differences. Heat exchangers are highly nonlinear, time-varying and show time lag behavior during operation. The temperature control of such processes has been challenging for control engineers and a variety of forms of PID controllers have been proposed to guarantee better performance. In this paper, a scheme to control the outlet temperature of a shell and tube heat exchanger system that combines the PID controller with feedforward control and anti-windup techniques is presented. A genetic algorithm is used to tune the parameters of the PID controller with anti-windup and the feedforward controller by minimizing the IAE (Integral of Absolute Error). Simulation works are performed to study the performance of the proposed method when applied to the process.

• 한국산학기술학회논문지
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• 제10권12호
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• pp.3581-3586
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• 2009

이 논문은 피드포워드 왜란상쇄 관측기를 이용하여 유도전동기의 강인한 제어를 얻을 수 있었다. 전통적인 비례적분 제어기의 속도응답 특징은 부하 토크 요소의 변이에 영향을 받는다. 제안한 시스템에서 속도제어 특성은 부하토크 외란에 영향을 받지 않는 피드포워드 제어를 사용하였다. 벡터제어를 위한 높은 속도의 계산과 처리를 위해 TMS320C31 디지털 프로세서를 사용하였다. 제안한 제어 방법의 타당성을 입증하기 위해 시뮬레이션과 실험을 통해 확인하였다.

• 한국전자파학회논문지
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• 제12권1호
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• pp.99-106
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• 2001

본 논문에서는 선형화 특성이 우수하고, 대역폭이 넓은 feedforward 선형화 기법을 이용하여 IMT-2000용 1-Watt 급 증폭기를 설계 제작하였다. Feedforward는 외부환경(온도, 입력 전력 레벨, 시간 등)의 변화에 민감하므로 마이크로컨트롤러를 이용하여 이를 제어하였다. 35dB 의 이득과 40dBm의 최고전력을 갖는 주증폭기를 설계하였고, 각 루프의 신호를 상쇄하기 위해서 반사형 가변감쇄기와 위상변화기를 사용하였다. 2.11 2.17GHz 대역에서 측정 결과 신호루프에서 주신호를 35dB이상 상쇄하였으며, 오차루프에서 30dB 이상 오차신호를 상쇄하여 60dBc 이상의 선형화 특성을 얻을 수 있었다.

• 전력전자학회논문지
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• 제9권3호
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• pp.253-259
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• 2004

본 논문은 BLDC 전동기의 고성능 속도제어를 위하여 외란 초크 관측기를 기반으로 한 속도 제어 방법에 대하여 기술하였다. 강성이 낮은 로봇 팔이나 추적 응용의 경우 시스템의 안정성 측면에서 속도 제어기의 이득 값을 크게 할 수 없다. 따라서 외란 토크 관측기를 이용한 전향 보상 방법을 이용하였다. 본 방법으로 속도 제어기의 이득을 충분히 크게 할 수 없을 때 외란 토크에 대한 속도 응답 특성을 향상시킬 수 있다. 결과적으로, 고성능 분야의 응용을 위한 BLDC 전동기의 속도 제어가 가능하게 된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.705-709
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• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• Journal of Power Electronics
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• 제15권4호
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• pp.1066-1073
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• 2015

This paper proposes a control strategy based on the frequency detection method, comprising a current control and a feed-forward voltage control loop, is proposed for grid-interactive power conditioning systems (PCS). For continuous provision of power to critical loads, PCS should be able to check grid outages instantaneously. Hence, proposed in the present paper are a frequency detection method for detecting abnormal grid conditions and a controller, which consists of a current controller and a feedforward voltage controller, for different operation modes. The frequency detection method can detect abnormal grid conditions accurately and quickly. The controller which has current and voltage control loops rapidly helps in load voltage regulation when grid fault occurs by changing reference and control modes. The proposed seamless transfer control strategy is confirmed by experimental results.

• 한국정밀공학회지
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• 제29권1호
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• pp.79-86
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• 2012

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.