• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.485-492
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• 2006

This paper deals with implementation of network for distributed control system of a humanoid robot ISHURO(Inha Semyung Humanoid Robot). A humanoid robot needs much degree of freedom structurally and much data for having flexible movement. To realize such a humanoid robot, distributed control method is preferred to the centralized one since it gives a compactness, modularity and flexibility for the controllers. For organizing distributed control system of a humanoid robot, a control processor on a board is needed to individually control the joint motor and communication technology between the processors is required to transmit its information within control time. The processor is DSP-based processor and includes CAN network on a chip. It shares the computational load such as monitoring the sensor information and controlling the actuator between each of modules. In this paper, the communication architecture is suggested and its message protocol are discussed including message structure, time consumption for transmission, and controller structure at the view of distributed control for a humanoid robot. All of the sequence are simulated with Matlab and then verified with real walking experiment by ISHURO.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.642-648
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• 2008

A lot of researches on the redundant manipulators have been focused mainly on the minimization of joint torques. However, it is well-known that the most dynamic control algorithms using local joint torque minimization cause huge torques which can not be implemented by practical motor drivers. A new control algorithm which reduces considerably such a huge-required-torque problem is proposed in this paper. It adapts fuzzy logic and genetic algorithm to the conventional local joint torque minimization algorithm. The proposed algorithm is applied to a 3-DOF redundant planar robot. Simulation results show that the proposed algorithm works well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3952-3958
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• 2011

This study was to investigate the difference in gait pattern between the visual handicap children and non handicap children in by analyze the biomechanical variation and pattern of lower limb. Therefore, we have made a choice of four visually handicapped children and two subjects, who had no medical disorder for the last six months. In order to collect the gait pattern data of each group, we have used six infrared cameras and one forceplate Also, we have used QTM program to collect the raw data and Visual3D program to calculate kinetic variable. The results were as follows, An/Posterior GRF of breaking phase and propulsion phase in stance phase was lower in visual handicapped children than that of non handicapped children and breaking phase was longer than propulsion phase. extension moment at the ankle was quite lower than general gait pattern and there was little variation at the knee joint which makes the results differ from the general gait pattern. However, hip joint moment was relatively higher than that of other joints. Mechanical variation of lower limb, in case of foot and shank, showed similar results. but generated very low mechanical energy. In thigh, the form of mechanical energy generation was slightly different in each group but generated more mechanical energy than other segments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.478-482
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) for robotic manipulators to achieve trajectorytracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adapation laws are derived from the improved second stability analysis based on the indirect adaptive control theory.l The proposed control scheme is simple in structure, fast in computation, an suitable for implementation of real-time control. Moreover, this scheme does not requre an accurate dynamic modeling, nor values of manipulator paramenters and payload Performance of the adaptive controller is illustrated by exeperimental results for a SCARA robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.385-393
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• 1999

An open loop vibrational control for an underactuated mechanical system with amplitude and frequently modulation is investigated. Since there is no direct external input to an unactuated joint, the dynamic coupling between the actuated and unactuated joints is utilized for controlling the unactuated joint. Feedback linearization has been performed to incorporate fully the known nonlinearities of the underactuated system considered. The actuated joints are firstly positioned to their desired locations, and the periodic oscillatory inputs are applied to the actuated joints to move the remaining unactuated joints to their target positions. The amplitudes and frequencies of the vibrations introduced are determined through averaging analysis. A systematic way of obtaining an averaged system for the underactuated system via a coordinate transformation is developed. A control design example of 2R planer manipulator with a free joint with no brake is provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.487-492
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method is composed of neural network of state space model type, performs for a unknown nonlinear system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.76-82
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• 2000

본 논문에서는 환경에 구속 받는 유연 매니퓨레이터의 힘/위치에 대하여 논하고자 한다. 일반적으로, 유연 매니퓨레이터의 모델링 방법은 분포 정수 모델과 집중 정수 모델로 분류할 수 있다. 전자인 분포 정수 모델을 이용해서는 평면 1 링크, 2 링크를 대상으로 한 위치/힘 제어는 가능하나, 운동 방정식의 복잡성으로 인하여 실시간에서 다 링크 다 관절 유연 매니퓨레이터의 힘/위치를 제어하기는 어렵게 여겨져 왔다. 본 논문에서는 집중 정수 모델링 방법인 집중 스프링 질량 모델(Lumped Spring Mass Model)을 이용하여 환경에 구속받는 유연 매니퓨레이터의 운동 방정식을 산출했다 이 모델을 실험기인 유연 매니퓨레이터 ADAM(Aerospace Dual Arm Manipulators)에 적용하여 실시간 위치/힘 제어 실험을 행하였으며, MATLAB를 이용하여 해석했다. 또한, ADAMS$^{TM}$ FEM를 이용하여 분포 정수 모델을 도출하여, 해석하였으며, 이 결과와 집중 정수 모델을 이용한 MATLAB 해석의 결과, 그리고 실험 결과를 비교 분석하여 본 논문에서 제안한 구속받는 유연 매니퓨레이터의 집중 정수 모델 타당성을 입증시켰다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.426-429
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• 2000

In this paper, we propose a system identification and control method using bias-modified neural network. The proposed method performs, for a nonlinear plant with unknown functions, system identification using bias-modified neural network, and then controller is designed with those identified informations. In order to verify the usefulness of the proposed method, we simulated the proposed control method with one link manipulator system and confirmed the excellency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.494-497
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method performs for a nonlinear system with unknown system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.