• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.15-20
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• 2001

In this paper, adaptive algorithms on the sliding model control for robust tracking control of robust manipulators are presented. The presented algorithms use adaption laws for tuning both the sliding mode gain and the thickness of the boundary layer to reject a disconitnuous control input, and to improve the tracking performance. It is shown that the robustness of the developed adaptive algorithms are guaranteed by the sliding mode control law and that the algorithms are globally convergent in the presence of disturbances and modeling uncertainties. Computer simulations are performed for a two-link manipulator, and the results show good properties of the proposed adaptive algorithms under large mainpulator parameter uncertainties and disturbances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.558-564
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• 2008

This paper presents an approach to combine adaptive controller with feedback linearization, which extends the applicability of the adaptive controller to a wider class of systems. The adaptive controller guarantees the asymptotic tracking convergence and the transient performance of the tracking error. The feedback linearization transforms a nonlinear plant into a linear time invariant form. The asymptotic tracking convergence is shown by the use of Lyapunov stability analysis and Barbalat's lemma.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.740-745
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• 2003

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• Journal of Welding and Joining
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• v.17 no.6
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• pp.90-99
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• 1999

Significant portion of the total manufacturing time for a pipe fabrication process is spent on the welding following primary machining and fit-up processes. To achieve a reliable weld bead appearance, automatic seam tracking and adaptive control to fill the groove are urgently needed. For the seam tracking in welding processes, the vision sensors have been successfully applied. However, the adaptive filling control of the multi-torches system for the appropriate welded area has not been implemented in the area of SAW(submerged arc welding) by now. The term adaptive control is often used to describe recent advances in welding process control by strictly this only applies to a system which is able to cope with dynamic changes in system performance. In welding applications, the term adaptive control may not imply the conventional control theory definition but may be used in the more descriptive sense to explain the need for the process to adapt to the changing welding conditions. This paper proposed various types of methodologies for obtaining a good bead appearance based on multi-torches welding system with the vision system in SAW. The methodologies for adaptive filling control used welding current/voltage, arc voltage/welding current/wire feed speed combination and welding speed by using vision sensor. It was shown that the algorithm for welding current/voltage combination and welding speed revealed sound weld bead appearance compared with that of voltage/current combination.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.51-60
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• 2005

This paper describes a robust control scheme for high-speed and long stroke scanning motion of high precision linear motor system consisting of linear motor, air bearing guide and position measurement system using heterodyne interferometer. Nowadays, semiconductor process and inspection of wafer or LCD need high speed and long travel length for their high throughput and extremely small velocity fluctuations or tracking errors. In order to satisfy these conditions, linear motor system are widely used because they have large thrust force and do not need motion conversion mechanisms such as ball screw, rack & pinion or capstan with which the system are burdened. However linear motors have a problem called force ripple. Force ripple deteriorates the tracking performances and makes periodic position errors. So, force ripple must be compensated. To maximize the tracking performance of linear motor system, we propose the control scheme which is composed of a robust control method, Time Delay Controller (TDC) and a feedforward control method, Zero Phase Error Tracking Control (ZPETC) for accurate tracking a given trajectory and an adaptive force ripple compensation (AFC) algorithm fur estimating and compensating force ripple. The adaptive ripple compensation is continuously refined on the basis of tracking error. Computer simulation results based on modeled parameters verify the effectiveness of the proposed control scheme for high-speed, long stroke and high precision scanning motion and show that the proposed control scheme can achieve a sup error tracking performance in comparison to conventional TDC control.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.582-590
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• 2007

Nonlinear adaptive control of overhead cranes is investigated for anti-sway trajectory tracking with high-speed hoisting motion. The sway dynamics of two dimensional underactuated overhead cranes is heavily coupled with the trolley acceleration, hoisting rope length, and the hoisting velocity which is an obstacle in the design of decoupling control based anti-sway trajectory tracking control law To cope with this obstacle. we propose a fuzzy nonlinear adaptive anti-sway trajectory tracking control law guaranteeing the uniform ultimate boundedness of the sway dynamics even in the presence of uncertainties in such a way that it cancels the effect of the trolley acceleration and hoisting velocity on the sway dynamics. In particular. system uncertainties, including system parameter uncertainty unmodelled dynamics, and external disturbances, are compensated in an adaptive manner by utilizing fuzzy uncertainty observers. Accordingly, the ultimate bound of the tracking errors and the sway angle decrease to zero when the fuzzy approximation errors decrease to zero. Finally, numerical simulations are performed to confirm the effectiveness of the proposed scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.12
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• pp.82-87
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• 2007

Excavator has been used in wide field since the attachment in the end effect can be changeable according to the purpose of working. However, efficiency of work using excavator mainly depends on an operator's ability. For the purpose of improving the efficiency of work and reducing the fatigue of operator, the automatic excavator system has been researched. In this paper, the tracking control system of each links of excavator is designed before developing the automatic excavator system. In order to apply the tracking control system, the pneumatic excavator system is developed and the tracking control system is applied. For designing the tracking control system, the adaptive sliding mode control algorithm is proposed. The performance of the proposed control system is evaluated through experiments using the pneumatic excavator system.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.334-336
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• 2008

A novel adaptive mesh refinement (AMR) strategy based on the Moment-of-Fluid (MOF) method for volume-tracking dynamic interface computation is presented. The Moment-of-Fluid method is a new interface reconstruction and volume advection method using volume fraction as well as material centroid. The mesh refinement is performed based on the error indicator, the deviation of the actual centroid obtained by interface reconstruction from the reference centroid given by moment advection process. Using the AMR-MOF method, the accuracy of volume-tracking computation with evolving interfaces is improved significantly compared to other published results.