• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2292-2295
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• 2001

In this paper, The control problem for a series DC motor is considered to adaptive fuzzy sliding-mode control scheme. Based on a nonlinear mathematical model of a series connected DC motor, instead of the combination of a nonlinear transformation and state feedback(feedback linearization) reduces the nonlinear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce computing time considerably.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.449-454
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• 2000

A new fuzzy logic control design algorithm suitable for multi-objective control problems is proposed based on the orthogonal array which is widely used for design of experiments in statistics and industrial engineering. The essence of the algorithm is to introduce Nth-certainty factor defined from the F-value of the ANOVA(analysis of variance) table, in order to effectively exclude the less confident rules. The proposed algorithm with multi-objective decision table(MODT) is found to be capable of the detection of inconsistency and the rule classification, reduction and modification. It is also shown that the algorithm can be successfully applied to the fuzzy controller design of an active magnetic bearing system.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.368-373
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• 2000

In this paper, a control algorthm suitable for multi-objective control is proposed based on the orthogonal array which is normally used in statics and industrial engineering. And a newly defined Nthcertainty factor is suggested, which can effectively exclude the less confident rule. The Nth-certainty factor is defined by the F-values of the ANOVA(analysis of variance) table. It is shown that the algorithm can be successfully adopted to the design of controller for an active magnetic bearing system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.417-420
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• 1990

The conventional quantitative techniques of system analysis are intrinsically unsuited for dealing with humanistic systems. Therefore, the rule based modeling of fuzzy linguistic type has been developed for the analysis of humanistic systems and complex systems and it is very significant for analysis and design of fuzzy logic controller. The activated sludge process is a commonly used method for treating sewage and waste waters. A mathematical tool to build a fuzzy model of the activated sludge process where fuzzy implications and linear reasoning are used is presented in here. A root-mean square error is used as the criterion of the fuzzy model's adequacy to the A.S.P. and the least square method is used for the identification of optimum consequence parameters. A method of modeling of the activated sludge process using its input-output data and simulation results for its application are shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.506-512
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modifY rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verifY the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.20-24
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• 2004

광범위한 네트워크의 연결과 이를 이용하는 조직이나 개인의 증가로 인터넷은 정보를 교환하고 거래를 수행하는 주요한 수단이 된 반면에 해커나 바이러스의 침입 또한 증가하여 공격에 쉽게 노출되어있다. 이러한 보안상의 문제점을 해결하기 위하여 컴퓨터나 네트워크 시스템의 활동을 감시할 수 있는 침입 탐지 시스템(IDS)과 같은 보안 요소를 도입하였으며, 탐지에 대한 성능을 향상시키기 위하여 네트워크를 기반으로 하는 다중 침입 탐지 시스템을 응용하여 네트워크에 분산된 에이전트들 중에서 발생된 침입에 알맞은 에이전트를 선택하도록 하여 침입 탐지를 효과적으로 할 수 있게 하였다. 본 연구에서는 보안 시스템의 연동을 위하여 계약망 프로토콜을 적용하였다. 계약망 프로토콜은 분산된 에이전트들 중에서 입찰과정을 통하여 최상의 에이전트를 선택하는데 이때, 에이전트를 선택하는 과정에 있어서 퍼지 규칙 기반 시스템을 적용한 퍼지 컨트롤러를 설계하여 시뮬레이션 한다.

• Smart Structures and Systems
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• v.20 no.1
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• pp.85-97
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• 2017

The aim of this research is to develop a new method to use magnetorheological (MR) damper for vibration control. It is a new way to achieve the MR damper response without the need to have detailed constant parameters estimations. The methodology adopted in designing the control structure in this work is based on the experimental results. In order to investigate and understand the behaviour of an MR damper, an experiment is first conducted. Force-displacement and force-velocity responses with varying current have been established to model the MR damper. The force for upward and downward motions of the damper piston is found to be increasing with current and velocity. In cyclic motion, which is the combination of upward and downward motions of the piston, the force with hysteresis behaviour is seen to be increasing with current. In addition, the energy dissipated is also found to be linear with current. A proportional-integral-derivative (PID) controller, based on the established characteristics for a quarter car suspension model, has been adapted in this study. A fuzzy rule based PID controller (F-PID) is opted to achieve better response for a varying frequency input. The outcome of this study can be used in the modelling of MR damper and applied to control engineering. Moreover, the identified behaviour can help in further development of the MR damper technology.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.1
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• pp.54-59
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• 2000

This paper presents a control system that uses a fuzzy algorithm in controlling the depth of a model midwater trawl net, and experimental results carried out in the circulating water channel by using a model trawl winch system.The fuzzy controller calculates the length of the warp to be changed, based on the depth error between the desired depth and actual depth of the model trawl net and the ratio of change in the depth error. The error and the error change are calculated every sampling time. Then the control input, i.e. desirable length of the warp, is determined by inference from the linguistic control rules which an experienced captain or navigator uses in controlling the depth of the trawl winch controller and the length of the warp is changed. Two kinds of fuzzy control rules were tested, one was obtained from the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.Two kinds of fuzzy control were tested, one was obtained fro the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.The results of these model experiments indicate that the proposed fuzzy controllers rapidly follow the desired depth without steady-state error although the desired depth was given in one step, and show robustness properties against changes in the parameters such as the change of the towing sped. Especially, a modified rule shows smaller depth fluctuations and faster setting times than those obtained by a field oriented rule.