• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1209-1217
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• 1997

This paper proposes the modeling of the dynamics of two cooperating robot manipulators performing the assembly job such as peg-in-hole while coordinating the payload along the desired path. The mass and moment of inertia of the manipulators and the payload are assumed to be unknown. To control the uncertain system, a robust control algorithm based on the computed torque control is proposed. Usually, the robust controller requires high input torques such that it may face input saturation in actual application. In this reason, the robust control algorithm includes fuzzy logic such that the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation while keeping path tracking errors bounded. A numerical example using dual three degree-of-freedom manipulators is shown.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1834-1835
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• 2006

A robust adaptive position control algorithm is proposed for servomotor drive system with uncertainties and load disturbance. The proposed controller is comprised of a nominal controller and a robust control. The nominal controller is designed in the condition without all the external load disturbance, nonlinear friction and unpredicted uncertainties. The robust controller containing lumped uncertainty approximator using fuzzy-neural network(FNN) is designed to dispel the effect of uncertainties and load disturbance. The interconnection weight of the FNN can be online tuned in the sense of the Lyapunov stability theorem thus asymptotic stability of the proposed control system can be guaranteed. Finally, simulation results verify that the proposed control algorithm can achieve favorable tracking performance for the induction servomotor drive system.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.428-431
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• 1995

In this paper we propose an on-line tuning method by using genetic algorithm for robust minimax I-PD controller based on new criterion. The new criterion is the Integral of Squared Error (ISE) with a penalty of the derivative of manipulated variable. The work focuses on robust tuning of I-PD controller's parameters in the presence of plant parameter uncertainty. The result of several simulation studies are provided to illustrate the performance of this robust tunig method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.974-988
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• 1995

In this paper, we propose a range image segmentation algorithm using robust regression. We derive a least $\kappa$th-order square (LKS) method by generalizing the least median of squares (LMedS) method and compare it with the conventional robust regressions. The LKS is robuster against outliers than the LMedS and shows performance similar to the residual consensus (RESC). The RESC uses the predetermined number of sorted residuals, whereas the LKS uses an adaptive parameter determined by given observations rather than the a priori knowledge. Computer simulation with synthetic and real range images shows that the proposed LKS algorithm gives better performance than the conventional ones.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.93-95
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• 2006

In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.237-242
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• 2012

One of the major problems for accurate channel estimation in power line communication systems is impulsive noise. Traditional channel estimation algorithms are based on the assumption of Gaussian noise, or the need to locate the positions of impulsive noise. The algorithms may lose optimality when impulsive noise exists in the channel, or if the location estimation of impulsive noise is inaccurate. In the present paper, an effective channel estimation algorithm based on a robust cost function is proposed to mitigate impulsive noise. The proposed method can provide a closed-form solution, and the application of robust estimation theory enables the proposed method to be free from localization of impulsive noise and thus can guarantee that the proposed method has better performance. Simulations verified the proposed algorithm.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.107-116
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• 2006

We propose a planning algorithm to automatically generate a robust behavior plan (RBP) with which mobile robots can achieve their task goal from any initial states under dynamically changing environments. For this, task description space (TDS) is formulated, where a redundant task configuration space and simulation model of physical space are employed. Successful task episodes are collected, where $A^*$ algorithm is employed. Interesting TDS state vectors are extracted, where occurrence frequency is used. Clusters of TDS state vectors are found by using state transition tuples and features of state transition tuples. From these operations, characteristics of successfully performed tasks by a simulator are abstracted and generalized. Then, a robust behavior plan is constructed as an ordered tree structure, where nodes of the tree are represented by attentive TDS state vector of each cluster. The validity of our method is tested by real robot's experimentation for a box-pushing-into-a-goal task.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.197-207
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• 2001

In this paper, design problem of QFT-PSS using Genetic Algorithm(GA) is investigated for power systems with parameter variation and disturbance uncertainties. A robust controller for uncertain power systems can be designed automatically such that the cost of feedback is minimized and all robust stability and performance specifications are satisfied. It is shown that the proposed design method not only automates loop shaping but also improves design quality and improves the quality with a reduced order controller. The robustness of the proposed controller has been investigated on a single machine infinite bus model. The results are shown that the proposed QFT-PSS using GA is more robust tan conventional PSS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.201-204
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• 2006

A system realization for real time DVR system with robust video watermarking algorithm against is attacked various is presented in this paper. The main system is composed of DSP processor and robust video watermarking to be processed at real time on image data and algorithm of the DVR system. The experimental result shows that the processing time takes about 2.5ms on the D1 size image per frame.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1019-1024
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• 2006

A system design and realization for real time DVR system with robust video watermarking algorithm for contents security is presented in this paper. The robust video watermarking is used the intraframe space region and interframe insertion simultaneously, and to be processed at real time on image data and algorithm is used the 64bits special purpose quad DSP processor with assembly and soft pipeline codes. The experimental result shows that the processing time takes about 2.5ms in the D1 image per frame for 60% moving image.