• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.41 no.2
• /
• pp.45-52
• /
• 2004

The sliding mode controller with a boundary layer implemented by simplified indirect inference method (SIIM) fuzzy logic was proposed. The components of the sliding line function are used for the inputs of the SIIM fuzzy logic. The proposed control system is simple because there is no need to derive the sigmoid function and there are only four rules. The overall stability of the proposed system and the boundness of the tracking error are proved easily using the Lyapunov theory. We apply the proposed controller to control a nonlinear time-varying system. The computer simulation showed the validity of the proposed control system.

• Journal of applied mathematics & informatics
• /
• v.40 no.5_6
• /
• pp.1043-1052
• /
• 2022

Our goal in this paper is to propose the advancement proposed by Alsina, Klement and other researchers in the area of fuzzy logic applied to the area of fuzzy graph theory. We introduce the notion of complete Hamacher fuzzy graphs and the notion of balanced Hamacher fuzzy graphs and discuss their properties. Moreover, several operations on these fuzzy graphs are explored via the complete notion.

• Industrial Engineering and Management Systems
• /
• v.4 no.2
• /
• pp.176-183
• /
• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• Journal of Computational Design and Engineering
• /
• v.3 no.1
• /
• pp.1-13
• /
• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.2
• /
• pp.153-159
• /
• 2009

The steel balls are core elements between inner part and outer part in a bearing system. The degree of goodness of the steel balls has been visually processed by human beings. In this paper we propose a new method that uses image processing algorithm and fuzzy logic theory. We use fuzzy inference engine and fuzzy Choquet integral algorithm in the proposed system. We first distinguish the defects of the steel balls by an image processing algorithm. And then the degree of the defects is classified by a fuzzy logic system. We perform some simulations to show the effectiveness and feasibility of the proposed system.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.206-209
• /
• 1999

Conventional target tracking techniques are primarily based on Kalman filtering or probabilistic data association(PDA). But it is difficult to perform well under a high cluttered tracking environment because of the difficulty of measurement, the problem of mathematical simplification and the difficulty of combined target detection for tracking association problem. This paper deals with an analysis of target tracking problem using fuzzy-logic theory, and determines fuzzy rules used by a fuzzy tracker, and designs the fuzzy tracker by using fuzzy rules and Kalman filtering.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.11a
• /
• pp.81-86
• /
• 1997

It is proposed, for fuzzy combustion control system of refuse incinerator to find the relationship between inputs and outputs and to generate rules to control by using rough set theory. It is not easy to find out the corresponding inputs for each output and the control rules with incomplete or imprecise information consisting expert knowledge, process and manipulator values in the field, and operation manual for the given system. Most decision problems can be formulated employing decision table formalism. A decision table on fuzzy combustion control system for refuse incinerator is simplified and produces control(rules). The I/O realtions and the control rules found by rough set theory are compared with the previous result.

• Journal of Mechanical Science and Technology
• /
• v.18 no.12
• /
• pp.2137-2147
• /
• 2004

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end-of-life phase. Disposal products have the uncertainties of product status by usage influences during product use phase, and recycling cells are formed design, process and usage attributes. In order to deal with the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. Fuzzy C-mean algorithm and a heuristic approach based on fuzzy ART neural network is suggested. Especially, the modified Fuzzy ART neural network is shown that it has a good clustering results and gives an extension for systematically generating alternative solutions in the recycling cell formation problem. Disposal refrigerators are shown as examples.

• Honam Mathematical Journal
• /
• v.37 no.3
• /
• pp.269-279
• /
• 2015

Atanassov introduced another fuzzy object, called intu- itionistic fuzzy set as a generalization of the concept of fuzzy subset. The aim of this paper is the elaboration of a representation theory of involutive interval-valued Łukasiewicz-Moisil algebras by using the notion of intuitionistic fuzzy sets.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.20-27
• /
• 1998