• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.105-109
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• 2001

This paper discuss the real-time self-tuning learning control based on evolutionary computation, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• Annual Conference of KIPS
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• 2015.04a
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• pp.212-213
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• 2015

Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. On constructing a robust algorithm for minimizing data aggregation delay in wireless sensor networks, we consider limited transmission range sensors and approximate the minimum-delay data aggregation tree which can only be built in networks of unlimited transmission range sensors. The paper proposes an adaptive method that can be applied to maintain the network structure in case of a sensor node fails. The data aggregation tree built by the proposed scheme is therefore self-healing and robust. Intensive simulations are carried out and the results show that the scheme could adapt well to network topology changes compared with other approaches.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.647-656
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• 2005

This paper proposes an adaptive resource self-management system that collects system resources, user information, and usage patterns as context information for utilization in self-configuration. This system ill ease the system maintenance burden on users by automation of large part of configuration tasks such as install, reconfiguration and update, and will also decrease cost and errors. Working from the gathered context information, this system allows users to select appropriate components and install them for user's system context. This also offers a more personalized configuration setting by using user's existing application setting and usage pattern. To avoid the overload on central server to transfer and manage related files, we employ Peer-to-Peer method. h prototype was developed to evaluate the system and a comparison study with the conventional methods of manual configuration and MS-IBM systems was conducted to validate the proposed system in terms of functional capacity, install time and etc.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1137-1147
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• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.47-55
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• 1990

An adaptive algorithm was applied to forecast daily stream flows in real time using rainfall data. A three-component tank model was selected to simulate the flows and its time-variant parameters were self-calibrated with updated data using a parameter optimization scheme, golden section search method. The resulting adaptive model, APTANK, was applied to six watersheds, ranging from 0.47 to 33.62 km$^2$ size and the simulated daily streamflows were compared with the measured. The simulation results were in good agreement with the field data. APTANK is found to be applied to real-time flow simulation purposes such as a tool for irrigation water resources management and operations. The model is particularly good to simulate streamflows on dry days as compared to wet days having runoff-induced precipitation.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.229-232
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• 2008

급격한 이동통신 기술의 발전에 힘입어 음영지역 해소 및 고속 데이터 처리를 위해 댁내 기지국에 대한 개발 및 연구가 진행 중이다. 댁내 기지국은 크게 음영지역 해소를 위한 Open 방식의 기지국과 고속 데이터 처리를 위해 특정 가입자만 사용할 수 있는 Close 방식이 있다. 상기 방식들은 망의 특성에 맞게 이를 제공하는 망 사업자에 의해 선택 된다. 댁내 기지국을 관리하기 위해서는 많은 시간과 인력자원이 소요되므로 자동으로 설정 및 최적화시키는 기능이 요구 시 되고 있으며, 이를 3GPP에서 SON (Self Organizing Optimizing Networks) 이라 일컫고 연구진행 중이다. 본 논문은 댁내 기지국 관리를 위해 셀의 기본 인자인 PCI(Physical Layer Identity) 할당 방안과 댁내 기지국간 간섭을 최소화 시키기 위한 Adaptive Coverage 방안을 제시한다. 또한 계층적 셀 구성(Hierarchical Cell Structure)에 따른 이동성 제공 방안을 제시한다.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1264-1267
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• 1987

In this study, a new implementation of an adaptive noise filter is proposed to eliminate timevarying 60Hz noise and its harmonics in ECG signal. The new technique was applied to the ECG and it was found in the experiment that it showed much better characteristics than conventional method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.54-59
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• 1998

In order to minimize straightness error of deflected shafts, a automatically bending process control system is designed, fabricated, and studied. The multi-step straightening process and the three-point bending process are developed for the geometric adaptive straightness control. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and studied for the three-point bending processes. Selection of a loading point supporting condition are derved form fuzzy inference and fuzzy self-learning method in the multi-step straighternign process. Automatic straightening machine is fabricated by using the develped ideas. Validity of the proposed system si verified through experiments.