• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.633-635
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• 1997

In this paper we present a scheme of adaptive backstepping controller for nonlinear system. Backstepping approach has recently been adopted as a design tool for nonlinear control and especially backstepping with modular design used to seperately design controller and identifier. In the modular design the nonlinear damping term is contained in controller for input-to-state stability (ISS). We compare the ISS controller, which used in general case, with the weak-ISS controller that attenuates the effect of nonlinear damping term and prove their advantages and disadvantages by simulation.

• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.65-77
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• 2003

This paper presents a model for supporting the adaptive interaction between the computer and the learner. To design an adaptive interaction model, the strategy to support the adaptive interaction in the web-based educational system was established. And then. the necessary components for executing each strategy were selected. Also. the logical relations among the components were verified. To verify the effectiveness of the proposed adaptive interaction model, we applied the existing web-based courseware and the new courseware using the adaptive interaction models to two groups respectively, and then measured the performance of each group. Experimental results reveal that the adaptive interaction model actually has positive effects on the learning activities of the learner.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.517-524
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• 1995

This paper is a study on the design of the cascade adaptive filter (CAF) for baseline wandering elimination in order to enhance the performance of the detection of ST segments in ECG. The CAF using Least Mean Square (LMS) algorithm consists of two filters. The primary adaptive filter which has the cutoff frequency of 0.3Hz eliminates the baseline wandering in raw ECG The secondary adaptive filter removes the remnant baseline wandering which is not eliminated by the primary adaptive filter. The performance of the CAF was compared with the standard filter, the recursive filter, and the adaptive impulse correlated filter (AICF). As a result, the CAF showed a lower signal distortion than the standard filter and the AICF. Also, the CAF showed a better perf'ormance in noise elimination than the standard filter and the recursive filter. In conclusion, considering the characteristics of the noise elimination and the signal distortion, the CAF shows a better performance in the removal of the baseline wandering than the other three Otters and suggests the high performance in the detection of ST segment.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.136-138
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• 1997

This paper proposes a design method to improve the performance of Indirect Adaptive Controllers using a CP net. This hybrid control architecture consists of Indirect Adaptive Controllers and CP net Controller. The performance of a single Adaptive Controller, multi Adaptive Controllers and the proposed model is compared by control problems. The simulation results show that the proposed model is superior to the others in most cases, in regard of not only learning speed but also control problems.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.140-146
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• 1995

In case the uncertainty existing in a system is assumed to satisfy the matching condition and to be come-bounded. Y. H. Chen proposed an adaptive robust control algorithm which introduced adaptive sheme for a design parameter into robust deterministic controls. In this paper, the adaptive robust control algorithm is applied to the position tracking control of direct drive robots, and simulation and experimental studies are conducted to evaluate control performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.7
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• pp.2067-2077
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• 1996

In adaptive finite element analysis, r- and h-methods are generally used on the basis of a discretization error estimator. In this paper, an rh-method is proposed as a new adaptive method which can improve the adaptivity performance by using both of them. This suggested rh-method moves nodal coordinates of initially given model to adjust element discretization errors and thereafter performes the h-method tdo obtain the specified accuracy of finite element solutions. Numerical experiments for various plane problems were performed using 4-noded isoparametric quadrilateral elements. As a result, the rh-method has been shown to be an accurate and efficient adaptive analysis method to obtain as improved solution.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2429-2432
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• 2000

Adaptive filter algorithm has been used for plant identifier and noise cancellation. This algorithm has been researched for performance enhancement of filtering. The design and development of a reliable system has been becoming a key issue in industry field because the reliability of a system is considered as an important factor to perform the system's function successfully. And the computing with reliability and fault tolerance is a important factor in the case of aviation and nuclear plant. This paper presents design of reliable adaptive filter with fault tolerance. Generally, redundancy is used for reliability. In this case it needs computing or circuit for voting mechanism or computing for fault detection or switching part. But this presented Filter is not in need of computing for voting mechanism, or fault detection. Therefore it has simple computing, and practicality for application. And in this paper, reliability of adaptive filter is analyzed. The effectiveness of the proposed adaptive filter is demonstrated to the case studies of plant identifier and noise cancellation by using DSP.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2019-2024
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• 2014

This paper presents a method to optimize the design of a planar-type antenna and reduce the number of design parameters for rapid computation. The electromagnetic characteristics of the structure are analyzed, and Taguchi method is used to identify critical design parameters. Adaptive particle swarm optimization, which has a faster convergence rate than particle swarm optimization, is used to achieve the design goal effectively. A compact dual-band USB dongle antenna is tested to verify the advantage of the proposed method. In this case, we can use only five selected geometrical parameters instead of eighteen to accelerate the optimization of the antenna design. The 10 dB bandwidth for return loss ranges from 2.3 GHz to 2.7 GHz and from 5.1 GHz to 5.9 GHz, covering all the WiBro, Bluetooth, WiMAX, and 802.11 b/g/n WLAN bands in both simulation and measurement. The optimization process enables the antenna design to achieve the required performance with fewer design parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.64.2-64
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• 2002

Contents 1. Introduction $\textbullet$ Contents 2. System description $\textbullet$ Contents 3. Desired feedback control and function approximation $\textbullet$ Contents 4. Robust adaptive controller design $\textbullet$ Contents 5. Simulation study $\textbullet$ Contents 6. Conclusion