• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.77-84
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• 2004

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown loads and the other uncertainties. The uncertainties are reflected in the performance index, where the uncertainties are bounded for the quadratic square of the states with a positive definite weighting matrix. An iterative algorithm is presented for the determination of the weighting matrix required for necessary robustness. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the simulation results shows that the proposed algorithm is very effective for a robust control of robotic systems.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.421-424
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• 1987

Recently, the problem associated with the achievement of desired trajectories for non-linear robotic manipulatory systems are researched. The control system which is designed for this robot manipulator, poses a number of severe problem. The methods proposed to deal with the problem fall loosely into three main classes : "direct" "adaptive", "anthropomorphic". Besides there is an approach which is described based upon the application of optimal control theory. In this paper, using the optimal theory, we choose error-coordinate, between the desired trajectories and the practical as the state values, and determine the control law U which minimize a corresponding performance criterion. Let's consider the robotic arm proposed by Freund and set up the deviations of it's trajectory as a measure of performance. To find the optimal control law $U^*$ and the next state value which need to obtain $U^*$ here, we should introduced the conjugate gradient algorithm and the Runge Kutta method.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.130-140
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• 2003

This paper presents an $H_\infty$controller synthesis based on disturbance observer for the trajectory control of a hydraulic excavator. Compared to conventional robot manipulators driven by electrical motors, hydraulic excavator have more nonlinear and coupled dynamics. In particular, the interactions between an excavation tool and the materials being excavated are unstructured and complex. In addition, its operating modes depend on working conditions, which make it difficult to not only derive the exact mathematical model but also design a controller systematically. In this study, the approximated linear model obtained through off-line system identification is used as nominal plant model for a disturbance observer. A disturbance observer based tracking controller which considers the effect of disturbance and model uncertainty is synthesized in $H_\infty$frameworks. Simulation results are used to demonstrate the applicability of the proposed control scheme.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.539-542
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• 1996

The forces exerted on an object by the end-effectors of multi-manipulators are decomposed into the motion-inducing force and the internal force. Motion-inducing force effects the motion of an object and internal force can't effect it. The motion of an object can't track exactly the desired motion because of internal force component, therefore internal force component must be considered. In this paper using the resolved acceleration control method and the fact that internal force lies in the null space of jacobian matrix, we construct independently the position, motion-inducing force and internal force controller. Secondly we construct the robust controller to preserve the robustness with respect to the uncertainty of manipulator parameters.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1761-1762
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• 2008

In this paper, we propose an adaptive neural control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. The dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. Simulation results for three-link electrically driven flexible-joint (EDFJ) manipulators are provided to validate the effectiveness of the proposed control system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.235-240
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• 1995

In order to eliminate position errors existing at the steady state in the motion control of robotic manipulators, a new fuzzy control algorithm is proposed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller. Three dimensional look-up table is used toreduce the computational time in real-time control, and a technique reducing the amount of necessary memory is introduced. Simulation and experimental studies show that the position errors at the steady state are decreased more than 90% compared to those of existing fuzzy controller when the proposed fuzzy controller is applied to the 2 axis direct drive SCARA robot manipulator.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.46-48
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• 1996

In almost all the servo systems, especially for the robot manipulators and numerical control systems, there are resonance effects and nonlinear frictions which should be considered in designing servo controllers. In this paper to compensate friction and track the step-input without steady-state error, the original system is augmented with an integrator and employes $\mu$-Controller design method $\mu$-Controller design method enables to meet not only performance requirements but robust stabilities simultaneously. And there may exist a limit cycles due to interaction between integrator and nonlinear friction. With describing function method, the possibility of limit cycle is checked.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.304-309
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the three dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The approaching of an insulator and the wrenching of a nut task is selected as the typical task of the maintenance of active electric power distribution lines in this paper. Image recognition by multilayer neural network and optimal target position calculation method are newly proposed in order to recognize the center 3 dimensional position of the bolt hole in the stand of insulator. By the proposed image recognition method, it is proved that the center 3 dimensional position of the bolt hole can be recognized rapidly and accurately without regard to the pose of the stand of insulator. Finally the approaching and wrenching task is automatically realized using 6-link electro-hydraulic manipulators.