• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.472-475
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• 1997

The principle objective of this paper is to explain and demonstrate the advantage of the output-feedback controller proposed by Ailon in [61 by using simulation and experimental results. Namely, the goal of this study is to design and implement a real-time controller for set-point regulation of a one-link rigid robot manipulator with unknown parameters using only position measurement. For implementation a direct drive one-link rigid robot manipulator is constructed and a TMS320C40 DSP systems board is used in implementing real-time control algorithm.

• 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 Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.6
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• pp.923-934
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• 1987

A flexible one-link robotic manipulator is modelled as a rotating cantilever beam with a hub and tip mass. An active control law is developed with consideration of the distributed flexibility of the arm. Equation of motion is derived by Hamilton's principle and, for modal control, represented as state variable form using Galerkin's mode summation method. Feedback coefficients are chosen to minimize the linear quadratic performance index(PI). To reconstruct the complete state vector from the measurements, an observer is proposed. In order to suppress vibration of the manipulator arm to desirable extent and to obtain accuracy of the positioning, weighting factor of input in PI is adjusted. Spillover effect due to the controller which controls several important modes is examined. Experiment is also performed to validate the theoretical analysis.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.204-209
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• 2004

This paper describes dynamic manipulability analysis of robotic arms moving in viscous fluid. The Manipulability is a functionality of manipulator system in a given configuration and under the limits of joint ability with respect to the tasks required to bt performed. To investigate the manipulability of underwater robotic arms, a modeling and analysis method are presented. The dynamic equation of motion of underwater manipulator is derived from the Lagrange - Euler equation considering with the hydraulic forces caused by added mass, buoyancy and hydraulic drag. The hydraulic drag term in the equation: is established as analytical form using Denavit - Hartenberg (D-H) link coordination of manipulator. Two analytical approaches based on Manipulability Ellipsoid are presented to visualize the manipulability of robotic arm moving in viscous fluid. The one is scaled ellipsoid which transforms the boundary of joint torque to acceleration boundary of end-effector by normalizing the torque in joint space while the other is shifted ellipsoid which depicts total acceleration boundary of end-effector by shifting the ellipsoid in work space. An analysis example of 2-link manipulator with proposed analysis scheme is presented to validate the method.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.50-59
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• 1998

This paper presents stabilization and adaptive control of flexible single link robot manipulator system by self-recurrent neural networks that is one of the neural networks and is effective in nonlinear control. The architecture of neural networks is a modified model of self-recurrent structure which has a hidden layer. The self-recurrent neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by feedback-error learning algorithm. When a flexible manipulator is rotated by a motor through the fixed end, transverse vibration may occur. The motor toroque should be controlled in such a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipuators so that it is arresed as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large changes in configuration common to robotic tasks requires dynamic models that describe both the rigid body motions, as well as the flexural vibrations. Therefore, a dynamic models for a flexible single link robot manipulator is derived, and then a comparative analysis was made with linear controller through an simulation and experiment. The results are proesented to illustrate thd advantages and imporved performance of the proposed adaptive control ove the conventional linear controller.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.688-695
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• 2005

This paper describes dynamic manipulability analysis of robotic arms moving in viscous fluid. The manipulability is a functionality of manipulator system in a given configuration under the limits of joint ability with respect to the task required to be performed. To investigate the manipulability of underwater robotic arms, a modeling and analysis method is presented. The dynamic equation of motion of underwater manipulator is derived based on the Lagrange-Euler equation considering with the hydrodynamic forces caused by added mass, buoyancy and hydraulic drag. The hydrodynamic drag term in the equation is established as analytical form using Denavit-Hartenberg (D-H) link coordination of manipulator. Two analytical approaches based oil manipulability ellipsoid are presented to visualize the manipulability of robotic arm moving in viscous fluid. The one is scaled ellipsoid which transforms the boundary of joint torque to acceleration boundary of end-effector by normalizing the torques in joint space, while the other is shifted ellipsoid which depicts total acceleration boundary of end-effector by shifting the ellipsoid as much as gravity and velocity dependent forces in work space. An analysis example of 2-link manipulator with proposed analysis scheme is presented to validate the method.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.205-212
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• 1999

A three dimensional binary parallel robot manipulator uses actuators which have only two stable states and its structure is variable geometry truss. As a result, it has a finite number of states and fault tolerant mechanism because of kinematic redundancy. This kind of robot manipulator has some advantages compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. Because the number of states of a binary robot manipulator grows exponentially with the number of actuators it is very difficult to solve and inverse kinematic problem. The goal of this paper is to develop an efficient algorithm to solve an inverse kinematic problem of three dimensional binary parallel robot manipulator using a backbone curve when the number of actuators are too much. We first derive the coordinate transformations associated with a three degree of freedom in-parallel actuated robot manipulator. The backbone curve is generated optimally by considering the maximum roll and pitch angles of the robot manipulator configuration and length of link. Then, the robot manipulator is fitted along the backbone curve with some criterion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.1-9
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• 1996

Although the fuzzy logic controller (FLC) has been adopted in many engineering applications, one hesitates to adopt the FLC in critical applications, since there was no definite control theoretic analysis. In this paper, based on the stability/robustness analysis of an FLC by S.Y.Yi$^{[3]}$, we apply the FLC to robot manipulator with the structured and unstructured uncertainties e.g., load variation and firction, etc. And we verify the performance of the FLC by computer simulation on a simple two-link robot manipulator.