• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.69.2-69
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• 2001

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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.998-1004
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• 2008

In this paper, a visual servoing control technique of humanoid robot arms is implemented for tracking a moving object. An embedded time-delayed controller is designed on an FPGA(Programmable field gate array) chip and implemented to control humanoid robot arms. The position of the moving object is detected by a stereo vision camera and converted to joint commands through the inverse kinematics. Then the robot arm performs visual servoing control to track a moving object in real time fashion. Experimental studies are conducted and results demonstrate the feasibility of the visual feedback control method for a moving object tracking task by the humanoid robot arms called the ROBOKER.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.234-239
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• 1993

Most of the control problem is for the redundant manipulators use the pseudo-inverse control, thit is, the redundancy is resolved by the pseudo-inverse of the Jacobian matrix and then the controller is designed based on this resolution. However, this pseudo-inverse control has some problems when the redundant robot repeats the cyclic tasks. This is because the pseudo-inverse resolution is a local solution that generates the different configurations of the robot arm for the same hand position. Therefore it is necessary to find the global solution that maintains the optimal configuration of the robot for the repetitive tasks. In this paper, we want to propose a redundancy resolution method by the optimal theory that uses the calculus of variation. The problem formulations are : first to convert the optimal resolution problem to an optimal control problem and then to resolve the redundancy using the necessary conditions of optimal control.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.119-128
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• 2015

In this paper, we propose a new motion control technology to design robust control system of industrial robot. The system modeling of robotic manipulation tasks with constraints is presented, and the control architecture for unconstrained and constrained motion system with parametric uncertainties is synthesized. The optimal reference of robot manipulator is generated by the reference controller as a discrete state system and the control behavior of constrained system which has poor modeling information and time-invariant constraint function is improved motion control system is successfully evaluated by experiment to the desired tasks.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.119.3-119
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• 2001

When building a network-based real-time control system, a network-induced delay time should be surly considered for real time schedulability to be guaranteed. The network delay time on end-to-end communication has been analyzed theoretically and modeled mathematically from many previous works. There also exist any other delay element not considered before. In this paper, the remote feedback control system using the CAN protocol is proposed to control three axes´ manipulator arm and the application layer of CAN is modeled to analyze the delay elements defined by three types of time delay: Software delay time, Controller delay time, and Access delay time, in details. The analyzed results are used as an important component to determine PID gains of the proposed system. The effect of the delay time on the control performance is evaluated by com paring the response characteristics of the control system through simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.5
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• pp.550-557
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• 2008

A transmission control cable connects the transmission control arm and the control lever mechanically and transfers control effort exerted by a driver to the transmission. It also transfers vibration generated by the engine to the passenger room through mechanical connection. To understand vibration and noise transfer mechanism and to further find a way to suppress the transmission of vibration effectively, a dependable dynamic vibration model is a necessity. A vibration model for a transmission control cable is developed and a simulation study has been conducted to obtain mode frequencies and a transmittability. The resonance frequencies obtained by an harmonic analysis is compared with the noise level measurement data. The measurement agrees with the simulation result thus ensures the reliability of the model.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.1-6
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• 1990

Neural network is a computational model of ft biological nervous system developed ID exploit its intelligence and parallelism. Applying neural networks so robots creates many advantages over conventional control methods such as learning, real-time control, and continuous performance improvement through training and adaptation. In this paper, dynamic control of a six-link robot will be presented using neural networks. The neural network model used in this paper is the backpropagation network. Simulated control of the PUMA 560 am shows that it can move a high speed as well as adapt to unforseen load changes and sensor noise. The results are compared with the conventional PD control scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1074-1080
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• 2015

In the last decades, the increasing interest in unmanned aerial vehicle(UAV) for military, surveillance, and rescue applications made necessary the development of flight control theory and body structure more and more efficient and fast. In this paper, we describe the design and performance of a prototype hexarotor UAV platform featuring an inertial measurement unit(IMU) based autonomous-flying for use in bluetooth communication environments. The proposed system comprises the construction of the test hexarotor platform, the implementation of an IMU, dynamic modeling and simulation in the hexarotor helicopter. Furthermore, the hexarotor helicopter with implemented IMU is connected with a micro controller unit(ARM-cortex) board. The P-PD control algorithm was used to control the hexarotor. We used the Matlab software to help us to tune the P-PD control parameters for quick response and minimizing the fluctuation. The control simulation and experiment on the real system are implemented in the test platform, evaluated and compared against each other.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.500-503
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• 1990

Neural network is a computational model of the biological nervous system developed to exploit its intelligence and parallelism. Applying neural networks to robots creates many advantages over conventional control methods such as learning, real-time control, and continuous performance improvement through training and adaptation. In this paper, dynamic control of a six-link robot will be presented using neural networks. The neural network model used in this paper is the backpropagation network. Simulated control of the PUMA 560 arm shows that it can move at high speed as well as adapt to unforseen load changes. The results are compared with the conventional PD control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.548-553
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• 2008

In this paper, we propose a new swing-up control strategy for rotary inverted pendulums with restricted rotation range. The control law is derived from a Lyapunov function. The Lyapunov function is defined as the square of the sum of the absolute value of the total mechanical energy and weighted squares of the arm's angular displacement and velocity. By adjusting the weighting parameters in the Lyapunov function, we can affect the swing-up strategy such that the restriction on rotation range can be satisfied. Finally, we verify the performance of the proposed control law through simulation and experiments.