• 한국산업융합학회 논문집
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• 제25권2_1호
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• pp.161-168
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• 2022

This study proposed a new approach to impliment a robusut control of comsumer-friendly flexible manipulator with five joint for untact working in filed work-site. The output redefinition approach was used to overcome the non minimum phase characteristic of the system. The new output is defined so that the zero dynamics related to this output are stable. The control strategy is based on an computed torque method which is applicable to a class of time-invariamt phase linear systems whose uncertainties appear in output loop stable. The controller is composed of a stabilizing joint controller and an output redefinition tracking controller. Experimental results are also presented to verify the effectiveness of the proposed control scheme.

• 한국통신학회논문지
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• 제14권5호
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• pp.486-502
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• 1989

본 논문에서는 로보트 매니퓰레이터의 정밀한 경로 제어를 위해서, 두가지 형태의 로보트 관절 각도 및 관절 속도의 예측 알고리즘을 제시하고, 이를 이용한 제어 방법을 기술하고자 한다. 구체적으로, 로보트 메니퓰레이터의 동특성을 Computed torque방법으로 선형화 시킨후에, 선형화된 모델을 근거로 한 이산시간 상태변수 예측기를 제안한다. 또한, 현재의 관절 위치 및 관절 속도와 과거 및 개의 위치 및 속도 등을 최소 자승법의 의미로 가장 잘 부합시키는 직선을 찾고, 그 직선으로부터 상태를 예측하는 예측기를 제안한다. 이 후에 이들 두 예측기로부터 정보를 이용하여, 예측된 궤적과 원하는 궤적 사이의오차에 적절한 이득을 곱해서 입력 토오크에 보정되어 사용됨으로써 궤적 오차를 줄일 수 있음을, 2자유도를 갖는 SCARA 로보트를 대상으로 컴퓨터 모의 실험을 통하여 보이고자 한다.

• 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.

• 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.

• 한국산업융합학회 논문집
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• 제21권1호
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• pp.37-44
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• 2018

In this work, a 4-DOF industrial robot system with three translational and one rotational motions which is widely used in palletizing applications is developed. In order for small robot manufacturing companies to develop their own robot systems for CNC machining and/or general automations, the analysis and design methods of a 4-DOF robot manipulator are presented and the development of a PC-based robot controller with EtherCAT are introduced. It is noted that the robot controller is developed by using Simulink Real-Time, which can provide an integrated environment of easier control algorithm development and data logging. Through position control and accuracy/repeatability measurement results, the developed robot prototype has comparable performances with commercial counterparts. In the future works, the advanced functions of industrial robots such as kinematic calibration, vibration suppression control, computed torque control, etc. will be investigated.

• 제어로봇시스템학회논문지
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• 제22권5호
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• pp.315-319
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• 2016

This paper proposes a simple adaptive sliding mode control algorithm for controlling a permanent magnet synchronous generator (PMSG) of a MW-class direct-driven wind turbine system. The proposed adaptive sliding mode controller does not require accurate knowledge of the PMSG parameter or turbine torque values. The proposed controller can accurately track the reference angular speed computed by the maximum power point tracking(MPPT) algorithm. Finally, this paper gives Matlab/Simulink simulation results to verify the practicality and effectiveness of the proposed adaptive sliding mode controller.

• 대한전자공학회논문지
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• 제25권8호
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• pp.916-926
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• 1988

In this paper, we explore real-time implementation of various dynamic control algorithms, which use the different levels of the information of the dynamics, using a SCARA type robot to show the feasibility and effectiveness of such algorithms. For these purposes, the kinematics of the SCARA type robot is anayzed and the manipulator-actuator dynamic equations based on Lagrange mechanisms are derived. Experimental results indicate that computed torque technique and iterative learning control methods perform better than classical PID control and that these algorithms can be effectively applied to controlling industrial manipulators.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.450-455
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• 1989

In this paper we investigate the application to the motion control of n-link robotic manipulators of recently developed stable factorization approach to tracking and disturbance rejection. Given control scheme consists of an approximate "Computed Torque" based upon a simplified model together with additional state feedback and feedforward compensation, and then, nonlinear control gain has more useful than constant control gain to guarantee robustness to parameter uncertainty and external disturbance. At this stage, we design high gain nonlinear state feedback controller and simulate this controller at the SCARA type robot manipulator of two joint.

• 제어로봇시스템학회논문지
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• 제4권1호
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• pp.10-18
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• 1998

불확실한 변수와 비선형성을 가지는 유연조인트 로봇의 견실제어 방안을 제시한다. 그리고 본 시스템에서 불확실구조는 일치성을 유지하지 않는 불일치성 불확실 시스템이다. 제어기는 리아노프의 방안에 근거를 두고있다. 견실제어는 연산토크법을 사용하고 삽입제어기법을 통하여 좌표변환을 통해 구성된다. 제어기 설계과정은 우선 연산토크방법에 의해 시스템 동역학에서 정격부분을 선형으로 2개의 부분시스템으로 구성한다. 이후 좌표변환을 이용하여 각 부분시스템에 제어기를 구축한다. 이 방안을 통하여 관성 행렬이 알려진 값인 경우 이 행렬의 상위한계 조건없이 제어기를 설계할 수 있다. 따라서 임의의 형태의 로봇에도 적용 가능한 제어알고리즘이 된다. 설계된 견실제어는 변환된 시스템이나 원시스템 모두 실용적 안정성을 보장한다. 이 변환은 단지 불확실변수의 최대 한계값의 정보만을 요구한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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• pp.2139-2142
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• 1997

The most important thing in vector control scheme is the knowledge of accurate electrical motor parameters. These parameters can computed by conventional motor test, such as no-load and locked rotor tests. However, the values from these tests are different from actual motor parameters, and the adjustment process of the parameters is time consuming. This paper presents an auto-tuning method for vector control of induction motor. The tuning algorithm is based on the rotor flux behavior of the induction motor for stepwise torque current command. The transient terminal voltage caused by the undesirable variation of the rotor flux is used for tuning the slip gain $K_5$ defined as the inverse of the rotor time constant. The electrical parameters of induction motor can also calculated by this method. The presented method is evaluated through the computer simulations.