• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.186-188
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• 1995

In this paper, Cross-Coupled Controller proposed for multi axes servo system. Tracking error and contouring error exist when a machine tool moves along the trajectory in multi exes system. The proposed scheme enhances the contouring performance by reducing contour error. Feedforward compensator reduces the effects of a nonlinear disturbance such as friction or dead zone. The proposed control scheme reduces the contour error which occured when the tool tracks the reference trajectory. Simulation results show that this scheme improves the contouring performance along the reference trajectory in XY-table.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.47-56
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• 2005

A new improved robust variable structure tracking controller is presented to provide an accurately prescribed tracking performance for brushless direct drive(BLDD) servo motors(SM) under uncertainties and load variations. A special integral sliding surface suggested for removing the reaching phase problems can define its ideal sliding mode and virtual ideal sliding trajectory from an initial position of SM. The tracking error caused by the nonzero value of the sliding surface is derived. A corresponding continuous control input with the disturbance observer is suggested to track a predetermined virtual ideal sliding trajectory within a prescribed value under all the uncertainties and load variations. The usefulness of the proposed algorithm is demonstrated through the comparative simulations for a BLDD SM under load variations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.230-235
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• 1992

We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

• Journal of Mechanical Science and Technology
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• v.15 no.4
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• pp.433-440
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• 2001

A new design of the sliding mode control is proposed for the uncertain linear time-varying second order system. The proposed control drives system states to the target point in the minimum time with specified ranges of parametric uncertainties and disturbances. One of the advantages of the proposed control scheme is that the control inputs do not go beyond saturation limits of the actuators. The other advantage is that the minimum arrival time and the acceleration of the second order actuators system can be estimated with given parametric bounds and can be expressed in the closed from; conversely, the designer can select actuators based on the condition of the minimum arrival time to the target point. The superior performance of the proposed control scheme to other sliding mode controllers is validated by computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.178-186
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• 1998

In this paper, a robust.adaptive learning control scheme is presented for precise trajectory tracking of rigid mobile robots. In the proposed controller, a set of desired trajectories is defined and used in constructing the control input and learning rules which constitute the main part of the proposed controller. Stable operating characteristics such as precise trajectory tracking, parameter estimation, disturbance suppression, etc., are shown thorugh experiments and computer simulations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.88-95
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• 2005

This paper presents a design scheme of model reference adaptive control incorporating a Neural Network for a pneumatic servo system. The parameters of discrete-time model of plant are estimated by using the recursive least square method. Neural Network is utilized in order to compensate the nonlinear nature of plant such as compressibility of air and frictions present in cylinder. The experiment of a trajectory tracking control using the proposed control scheme has been performed and its effectiveness has been proved by comparing with the results of a model reference adaptive control.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.29-34
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• 2013

This study presents the remote control of a mobile robot using iPhone based on ad hoc communication. Two control interfaces are proposed to control a mobile robot using iPhone : Remote control by a user and autonomous control. To evaluate the effectiveness of algorithms for trajectory following, a simulator are developed where a virtual robot follows a referenced trajectory in a monitor by iPhone interface. In the proposed simulator, some algorithms are tested how they work well or not for trajectory following of a mobile robot. Comparative results by remote user control and autonomous control are shown. Results of an experiment show that the proposed simulator can be effectively used for testing the effectiveness of autonomous tracking algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.540-543
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• 1997

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of the path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force, and external disturbance are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the usage of vision system makes mobile robot compensate the cumulative location error which exists when relative sensor like encoder is used to locate the position of mobile robot. The effectiveness of the proposed control scheme is shown through computer simulation.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1614-1619
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• 2003

In this study, position and force simultaneous trajectory tracking control system with pneumatic cylinder driving apparatus is proposed. The pneumatic cylinder driving apparatus that consists of two pneumatic cylinders constrained in series and two proportional flow control valves offers a considerable advantage as to non-interaction of the actuators because of the low stiffness of the pneumatic cylinders. The controller applied to the driving system is composed of a non-interaction controller to compensate for interaction of two cylinders and a disturbance observer to reduce the effect of model discrepancy of the driving system in the low frequency range that cannot be suppressed by the non-interaction controller. The experimental results with the proposed control system show that the interacting effects of two cylinders are eliminated remarkably and the proposed control system tracks the given position and force trajectories accurately.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.177-182
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• 2013

This paper proposes an input-constrained reference tracking control of a converter model. To this end, first it is shown that the bilinear converter model can be equivalently represented by a linear uncertain model belonging to a polytopic set. Then, an input-constrained tracking control scheme for the linear uncertain model is designed based on recently proposed tracking control scheme. The control scheme yields not only a stabilizing control gain but also a feasible and invariant set for the converter model. Finally, simulation results show that the state trajectory always stays in the feasible and invariant set and that the output tracks the given reference while satisfying the input constraint.