• 대한기계학회논문집
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• 제15권1호
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• pp.145-153
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• 1991

본 연구에서는 Toh가 개발하여 stretchforming에 응용한 강소성 대변형 이론 을 압연문제에 적용하여 강소성 대변형 유한요소 프로그램을 개발하는데 있다.

• 동력기계공학회지
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• 제16권3호
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• pp.57-63
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• 2012

본 논문은 작업공간상에서 로봇 운동과 힘의 통합제어를 구현할 수 있는 플랫폼의 구현에 초점을 두고 있다. 조립 또는 디버링 같은 접촉작업에서의 매니플레이터 효율성 제고나 친 인간 환경에서의 휴머노이드 로봇의 안정성을 위해서는 종래의 PID 제어나 관절공간상에서의 CTM(Computed Torque Method) 제어보다는 작업공간상에서의 운동과 힘의 통합제어를 실시해야 한다. 이것을 위해서는 작업공간상에서의 엔드이펙트(end-effector, E-E)에 대한 동역학식과 자코비안(jacobian)을 도출해야 하며 이를 위해서는 각종 동적파라미터의 정확한 동정이 중요하다. 본 논문에서는 3D CAD 모델링, MATLAB, 동역학 시뮬레이터를 활용하여 로봇 모델링, 동역학식과 동적 파라미터 추출, 운동과 힘의 실시간 통합제어 시뮬레이션등을 쉽고 일관되게 진행할 수 있는 플랫폼을 구현하였고 적용예로써 JS-10로봇을 택해서 그 효용성을 입증하였다.

• 제어로봇시스템학회논문지
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• 제5권1호
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.445-449
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• 1993

The role of a robot becomes more important as factory automation is widely spread in the manufacturing industry. An off-line program system has been required for uninterruption of production lines because it can save cost and time spent in adjusting a robot to a new workcell. The objective of this paper is to develop our own OLP system for a SCARA type FARA robot with four axes. Three-dimensional graphic results are presented for the case when the robot is simulated using the computed torque method with a PD controller and the continuous path trajectory planning.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 하계종합학술대회 논문집
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• pp.675-678
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• 1989

This paper proposes two types of the preview algorithms to predict the joint velocities and joint positions, and deals with a control approach using the preview algorithms for the precise trajectory control. Specifically, a predictor an the form of discrete time state equations is proposed based on the robot dynamics model linearized by the computed torque method. And another state predictor is proposed by the beat line fitting in the least square sense, where present joint velocities and positions and several past positions are employed. Then computer simulations are performed for the SCARA robot with two d.o.f. to show the validities of the proposed algothrithms.

• 한국생산제조학회지
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• 제22권2호
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• pp.185-191
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• 2013

In this paper, the dynamics of a novel 2-DOF planar Translational Parallel Manipulator (TPM) is analyzed. The suggested TPM is made up of two PPa (Prismatic-planar Parallelogram) legs. Since all the linear actuators are mounted on the base, the proposed TPM can be applied for high speed positioning applications. The Lagrangian equations of the first type is employed to derive the inverse dynamic equations. It is shown that the analytical inverse dynamics equations match very well with ADAMS simulations. These analytical inverse dynamics equations will be used for the real-time computed torque control in the further work.

• 제어로봇시스템학회논문지
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• 제1권2호
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• pp.88-93
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• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권7호
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• pp.380-388
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• 2006

In this paper, a novel control algorithm to minimize the power loss of the induction generator for wind power generation system is presented. The proposed method is based on the flux level reduction, where the flux level is computed from the machine model for the optimum d-axis current of the generator. For the vector-controlled induction generator, the d-axis current controls the excitation level in order to minimize the generator loss while the q-axis current controls the generator torque, by which the speed of the induction generator is controlled according to the variation of the wind speed in order to produce the maximum output power. Wind turbine simulator has been implemented in laboratory to validate the theoretical development. The experimental results show that the loss minimization process is more effective at low wind speed and that the percent of power loss saving can approach to 25%. Experimental results are shown to verify the validity of the proposed scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.12-14
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• 1999

The paper is described about the characteristics analysis of Axial Fluk Reluctance Motor(AFRM) with nonlinear analytical modeling. The parameter of the modeling is computed by the finite element method as functions of input current and angular displacement. To investigate the dynamic characteristics of AFRM, the current, torque, back EMF and output power wave is simulated from the motion equation by MATLAB/Simulink.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.193-196
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• 1999

This paper presents a new systematic contingency selection and screening method for transient stability. The variation of modal synchronizing torque coefficient(MSTC) is computed using eigen-sensitivity analysis of the electromechanical oscillation modes in small signal stability model and contingencies are ranked in decreasing order of the sensitivities of the MSTC(SMSTC). The relevant clusters are identified using the eigenvector or participating factor. The proposed algorithm is tested on the KEPCO system. Ranking obtained by the SMSTC is consistent with the time simulation results by PSS/E.