• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.463-466
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this paper, to field-robotize a hydraulic excavator, we have proposed a robust and systematic controller design method. Disturbance observer is used as inner controller to reshape the excavating system into the linear dynamics of nominal model by compensating coupled nonlinear terms, model uncertainties and external load variations. Using the linear model that is obtained through off-line system identification, a H control scheme is applied to construct a disturbance observer and a servo-controller systematically.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.403-411
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• 2015

In this paper, we propose a design method for the position and speed controller, current control of a Brushless Direct Current(BLDC) motor using back-stepping design techniques. Further, to stabilize the whole system, and proposes a method for setting the appropriate gain control to improve the tracking performance. By applying the proposed controller to 120W BLDC motors were tested for the ability to follow the position, velocity and current reference. Since the simulation results of the steady state error is within 1%, we were able to show the usefulness of the tracking performance of the proposed controller.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.10
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• pp.1359-1366
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• 2010

Recently, many electronic control techniques for vehicles have been developed and applied. One of the technologies can be X-by-wire such as throttle-by-wire, brake-by-wire, steer-by-wire, and etc, in which most of mechanical parts are replaced into electrical wire and actuators. In this study, the effect of throttle-by-wire and brake-by-wire control systems on vehicle velocity control, especially in a school zone, are taken into consideration. The number of accidents reported in school zones is higher than that in other places. The reason for this is that many vehicle drivers do not obey speed limit regulations. Moreover, some of the students are careless while crossing the streets. Therefore, in this study, we attempt to develop a method using throttle-by-wire and brake-by-wire control systems for automatically reducing the vehicle speed such that it will be within the speed limit. First, an engine model and a transmission system model are developed for a specific vehicle model. Second, speed reduction is carried out such that the reduction follows a pre-designed cubic spline trajectory; the trajectory is determined such that rapid deceleration, which causes discomfort to the driver and passengers, can be prevented, for which a fuzzy-PID control algorithm is applied for the trajectory following control. Finally, simulation results are presented to verify the performance of the proposed speed reduction control system.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2862-2864
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• 2000

네트워크 환경의 보편화와 함께 원격강의와 가상실험에 대한 연구가 진행되고 있다. 로봇공학교육에 있어서 가상현실은 가상실험을 구현하기 위한 밑바탕이 되며 값싸고 위험부담없이 실제실험과 유사한 환경을 구축하기 위한 도구가 된다. 본 논문에서는 월드와이트웹 상에서 동작가능하며 다양한 궤적과 제어기를 사용자가 조작하면서 비교 학습 할 수 있는 로봇제어 학습용 시뮬레이터를 개발한다. 가상로봇은 실제로봇과 유사한 특징을 가지며 게인값 설정에 따른 궤적추종을 로봇의 움직임으로 관찰할 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.9-15
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• 1998

This paper presents an adaptive learning control method for unknown nonlinear systems by combining neuro control and iterative learning control techniques. In the present control system, an iterative learning controller (ILC) is used for a process of short term memory involved in a temporary adaptive and learning manipulation and a short term storage of a specific temporary action. The learning gain of the iterative learning law is estimated by using a neural network for an unknown system except relative degrees. The control informations obtained by ILC are transferred to a long term memory-based feedforward neuro controller (FNC) and accumulated in it in addition to the previously stored infonnations. This scheme is applied to a two link robot manipulator through simulations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.19-25
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• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.239-239
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• 2000

This paper present experimental results on temperature trajectory tracking. The benefits of precalculated feedforward input together with PID feedback control are demonstrated by experimental results. To find the feedforward input, the plant (autoregresiive) model is first identified and convex optimization procedure is applied. PID controller is then implemented based on Ziegler-Nickels tuning rule to reduce effects of disturbances and modeling errors. Experimental results show an improvement in slope tracking performance over the fully PID controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.466-471
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• 1994

To make a dynamic system a given desired motion trajectory, a new feedback error learning scheme is proposed which is based on the repeatability of dynamic system motion. This method is composed of feedforward and feedback control laws. A benefit of this control scheme is that the input pattern that generates the desired motion can be formed without estimating the physical parameters of system dynamics. The numerical simulations show the good performance of the proposed scheme

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.9-16
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• 2018

Predictive control is a very practical method that obtain the current input that minimizes the future errors of the reference command and state by use of the predictive model of the controlled object, and can also consider the constraints of the state and input. Although there have been studies in which predictive control is applied to mobile robots, performance has not been optimized as various control parameters for determining control performance have been arbitrarily specified. In this paper, we apply the genetic algorithm to the trajectory tracking control of a mobile robot with input constraints in order to minimize the trajectory tracking errors through control parameter tuning, and apply the quadratic programming Hildreth method to reflect the input constraints. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.

• Journal of IKEEE
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• v.22 no.1
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• pp.110-120
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• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.