• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1785-1789
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• 1991

Recently, a number of papers on adaptive control scheme of manipulators are proposed. Slotine and Li[1] showed an adaptive control scheme for robot manipulator. The controller was described in closed form. And later Niemeyer and Slotine discussed about a computational implementation of the controller in recursive form[2]. Walker proposed another adaptive control scheme which can be implemented by a recursive-form controller[4]. Closed-form description is used for the analysis or design of adaptive control systems while recursive-form realization is used for implementation of the controller. The relation between the closed-form realization and the recursive-form one seems to be inadequately referred. Hence, it makes sense to consider the relation between the closed-form description and the recursive-form one. In this paper, first, we make a simple derivation of an closed-form dynamics description of a robot arm from its recursive-form description. And then we derive the closed-form realization of Walker's scheme applied to manipulators having no kinematic loop. We clarify the difference between the Walker's scheme and Slotine's and evaluate the convergence under the controllers.

• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.279-286
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• 1996

In this paper, variable structure control(VSC) based on reaching law method with fuzzy inference for nonlinear systems is proposed. The reaching law means the reaching condition which forces an initial state of system to reach switching surface in finite time, and specifies the dynamics of a desired switching function. Since the conventional reaching law has fixed coefficients, the chattering can be existed largely in sliding mode. In the design of a proposed fuzzy reaching law, we fuzzify RP(representative point)'s orthogonal distance to switching surface and RP's distance the origin of the 2-dimensional space whose coordinates are the error and the error rate. The coefficients of the reaching law are varied appropriately by the fuzzy inference. Hence the state of system in reaching mode reaches fastly switching surface by the large values of reaching coefficients and the chattering is reduced in sliding mode by the small values of those. And the effectiveness of the proposed fuzzy reaching law method is showen by the simulation results of the control of a two link robot manipulator.

• 한국산학기술학회논문지
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• 제13권4호
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• pp.1453-1459
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• 2012

본 연구에서는 보이스코일 모터와 압전 구동기를 동일 축으로 배치함으로써 초정밀 위치결정뿐만 아니라 동특성을 개선할 수 있도록 하는 듀얼 스테이지를 다룬다. 듀얼 스테이지는 모델링이 엉성할 경우 오히려 나쁜 동특성을 보이는 단점이 있다. 이 논문은 본드그래프를 이용하여 듀얼 스테이지를 모델링하고 동적 상태방정식을 본드그래프에서 유도하였다. 또한 동특성을 향상시키기 위한 보상기의 설계 예시를 보이고 있으며, 시뮬레이션을 통해 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.610-615
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• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.626-630
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• 2005

This paper presents a novel Intelligent-Welding-Carriage (IWC) for automation of curved block in shipbuilding. The curved block is usually used in both front and back side of the ship. In curved block root gap is big, $1{\sim}7$ [mm] and inclination, $0{\sim}30$ [deg]. Since available conventional carriage type is limited to use below root gap of 3 [mm], only manual welding is employed in curved block. To adopt an IWC in curved block, it requires control of the welding conditions, i.e., voltage, current and travel speed, with respect to root gap and inclination to achieve good welding quality. In this paper, an IWC is developed for automization of welding operation to accommodate gap and inclination. Kinematics model and dynamics using Lagrangian formulation of the manipulator is introduced. IWC utilizes a database to perform accurate welding. The database is programmed based on numerous experimental test results with respect to gap, inclination, material, travel speed, weaving condition, voltage, and current. Finally, experimental result using PID control is addressed for verify the trajectory tracking accuracy of end-effector.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.963-968
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• 1990

An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.

• 전자공학회논문지SC
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• 제38권6호
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• pp.28-36
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• 2001

피드-포워드 보상부분과 불연속 제어 부분으로 구성되는 강건한 적응 슬라이딩 모드 로봇제어 알고리즘을 유도하였다. 미지의 매개변수는 실시간으로 추정되는 매개변수를 포함하는 그룹과 실시간으로 추정하지 않는 매개변수를 포함하는 그룹으로 나누어진다. 그런 다음 외란 및 실시간으로 추정하지 않는 매개변수에서의 불확실성 효과를 보상하기 위해 슬라이딩 제어 항이 토크 입력에 포함된다. 또한 매니퓨레이터 동역학 구조의 효율적인 이용으로 인하여 알고리즘은 계산이 간단하다. 매개변수 불확실성과 외부 외란의 존재에도 불구하고 제어기는 대국적 점근적으로 안정하며 추적오차가 영에 수렴함을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.