• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.963-968
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• 1990

An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2017-2024
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• 2020

In this study, a fractional order proportional integral derivative (FOPID) controller is designed to create the reference power trajectory and to conquer the uncertainties and external disturbances. A fractional nonlinear model was utilized to describe the nuclear reactor dynamic behaviour considering thermal-hydraulic effects. The controller parameters were tuned using optimization method in Matlab/Simulink. The FOPID controller was simulated using Matlab/Simulink and the controller performance was evaluated for Hard variation of the reference power and compared with that of integer order a proportional integral derivative (IOPID) controller by two models of fractional neutron point kinetic (FNPK) and classical neutron point kinetic (CNPK). Also, the FOPID controller robustness was appraised against the external disturbance and uncertainties. Simulation results showed that the FOPID controller has the faster response of the control attempt signal and the smaller tracking error with respect to the IOPID in tracking the reference power trajectory. In addition, the results demonstrated the ability of FOPID controller in disturbance rejection and exhibited the good robustness of controller against uncertainty.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.261-262
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• 2007

This paper proposed a model algorithm control (MAC) method for trajectory tracking control of the differentially steeredwheeled mobile robots (WMRs) subject to nonholonomic constraint. The dynamic model of the wheeled mobile robot is presented and used as the model to be controlled. The performance of the proposed control algorithm is verified via computer simulations in which the WMR is controlled to track several different reference paths. It is shown that the control strategy is feasible.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.380-384
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• 1996

This paper represents an adaptive position controller with the disturbance observer for multi-axis servo system. The overall control system consists of three parts : the position controller, the disturbance observer with free parameters and cross-coupled controller which enhances contouring performance by reducing errors. Using two-degrees-of freedom conception, we design the command input response and the closed loop characteristics independently. The servo system can improve the closed loop characteristics without affecting the command input response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer. Moreover, the cross-coupled controller enhances tracking performance. Thus total position control performance is improved. Finally, the performance of the proposed controller shows that it improves the contouring performance along with the reference trajectory in the XY-table.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.301-306
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• 2021

In this paper, we propose a modified back-stepping control method in view of the dynamic model of mobile manipulator has the nonholonomic constraints, these constraints should be considered to design a tracking controller for the mobile manipulator. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot systems. and the modified adaptive back0stepping method is applied to constructing the controller. The proposed controller can realize the tracking trajectory of the reference path. The efficiency and robustness of this control method is demonstrated by the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.177-182
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• 1989

In this paper a new adaptive control algorithm is derived, with the unknown manipulator and payload parameters being estimated online. In practice, we may simplify the algorithm by not explicity estimating all unknown parameters. Further, the controller must be robust to residual time-varying disturbance, such as striction or torque ripple. Also, the reference model is a simple douple integrator and the acceleration input for robot manipulator consists of a proportion and derivative controller for trajectory tracking purposes. The validity of this control is confirmed in simulation where two-link robot manipulator shows the robust performances in spite of the existing nonlinear interaction and unknown parametrictings

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1834-1847
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• 2006

A robust minimum-time control (RMTC) strategy is addressed and it is extended to the dual-stage servo design. Rather than conventional switching type sub-optimal controls, it is a reference following control approach where the predetermined minimum-time trajectory (MTT) is tracked by the perturbation compensator based feedback controller. First, the minimum-time trajectory for a mass-damper system is derived. Then, the perturbation compensator to achieve robust tracking performance in spite of model uncertainty and external disturbance is suggested. The RMTC is also applied to the dual-stage positioner which consists of coarse actuator and fine one. To best utilize the actuation redundancy of the dual-stage mechanism, a null-motion controller to actively regulate the relative motion between the two stages is formulated. The performance of RMTC is validated through simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.363-368
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• 2005

This paper proposes an LOS(line-of-sight) guidance system of a ship for path following. From the viewpoint of a control configuration, guidance is a special type of compensation algorithm that is placed in front of the controller to accomplish navigational objects. A guidance system generates a reference trajectory for trajectory tracking or path control and decides the desired velocity, position and heading angle. A control system executes commands based on a reliable guidance law during navigation. An LOS vector from the vessel to a point on the path between two way-points in straight-line navigation or a point among turning circle in turning navigation is selected, and then a heading angle is calculated to converge the desired path based on the LOS vector. The LOS guidance law is defined for the straight-line and the turning circle, respectively. The effectiveness of the suggested LOS guidance system is assured through computer simulation.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.65-68
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• 1995

This paper describes trajectory generation of a riobot arm by self-organizing neural networks. These neural networks are based on competitive learning without a teacher and this algorithm which is suitable for problems in which solutions as teaching signal cannot be defined-e.g. inverse dynamics analysis-is adopted to the trajectory generation problem of a robot arm. Utility of unsupervised learning algorithm is confirmed by applying the approximated solution of each joint calculated through learning to an actual robot arm in giving the experiment of tracking for reference trajectory.