• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.3
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• pp.32-48
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• 1994

This paper proposes the compensation algorithm of conventional shift pattern using fuzzy reasoning in automatic transmission vehicles. Recently, automatic transimssion vehicles are continually increasing because of theire ease to drive. Also users require the high performance which includes the smooth shift quality and shift scheduling that matches driver;s intentions. So the shift scheduling has been inproved significantly through the application of electronic control. But, in spite of this development, vehicles using conventional shift pattern are sometimes in discord with driver's intention on roads. In this paper, the paper, the proposed compensation algorithm makes a automatic transmission vehicle be able to select an optimal gear shifting time and position using fuzzy reasoning and make a vehicle driver feel confortable even when the vehicle runs on roads which is extremely changed. Therefore, a vehicle driver can expect to reduce the nimber of unnecessary gear shifting and expect the fuel efficiency high. To show usefulness of the proposed method, some simulation are made to compared with conventional gear shifting. Paper prosposes the compensation mehtod of conventional shift pattern using fuzzy reasoning for the purpose that a vehicle can select an optimal gerar shifting time and position in automatic vehicle. Though the conventional shift pattern has no pliability, vehicle driver can feel comfortable and can reduce the number of unnecessary gear shifting using the proposed method on variable road condition. Therefore, it can be expected the fuel efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.174-179
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• 2009

We consider the stabilization problem for a class of networked control systems with neutral type of time delays. The neutral type of time-delays occur in controller-to-actuator and sensor-to-controller. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with neutral type of time-delays. The stabilization via state-feedback is first addressed, and delay-range-dependent stabilization conditions are proposed in terms of linear matrix inequalities (LMIs). Finally, an application example will be given to show the merits and design a procedure of the proposed approach.

• Ocean Systems Engineering
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• v.5 no.3
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• pp.161-179
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• 2015

An emergency response system (ERS) for vessel oil spills is a complex and dynamic system comprising a number of subsystems and activities. Failures may occur during the emergency response operations, this has negative impacts on the effectiveness of the ERS. Of the classes of problems in analyzing failures, the lack of quantitative data is fundamental. In fact, most of the empirical data collected via questionnaire survey is subjective in nature and is inevitably associated with uncertainties caused by the human being's inability to provide complete judgement. In addition, incomplete information and/or vagueness of the meaning about the failures add difficulties in evaluating the effectiveness of the system. Therefore this paper proposes a framework to evaluate the ERS effectiveness by using the combination of fuzzy reasoning and evidential synthesis approaches. Based on analyzing the procedure of ERS for oil spills, the failures in the system could be identified, using Analytic Hierarchy Process(AHP)to determine the relative weight of identified failures. Fuzzy reasoning combined with evidential synthesis is applied to evaluate the effectiveness of ERS for oil spills under uncertainties last. The proposed method is capable of dealing with uncertainties in data including ignorance and vagueness which traditional methods cannot effectively handle. A case study is used to illustrate the application of the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.167-175
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• 2021

Reusing electric vehicle batteries after they have been retired from mobile applications is considered a feasible solution to reduce the demand for new material and electric vehicle costs. However, the evaluation of the value and the performance of second-life batteries remain a problem that should be solved for the successful application of such batteries. The present work aims to estimate the remaining useful life of Li-ion batteries through the neuro-fuzzy system with the equivalent circuit parameters obtained by Electrochemical Impedance Spectroscopy (EIS). To obtain the impedance spectra of the Li-ion battery over the life, a 18650 cylindrical cell has been aged by 1035 charge/discharge cycles. Moreover, the capacity and the parameters of the equivalent circuit of a Li-ion battery have been recorded. Then, the data are used to establish a neuro-fuzzy system to estimate the remaining useful life of the battery. The experimental results show that the developed algorithm can estimate the remaining capacity of the battery with an RMSE error of 0.841%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.28-31
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• 2003

In the present work, a main purpose is to propose a fuzzy integral-based aggregation framework to complementarily combine partial information due to lack of completeness. Based on Choquet integral (CI) viewed as monotone expectation, we take into account complementary, non-interactive, and substitutive aggregations of different sources of defective information. A CI-based system representing upper, conventional, and lower expectations is designed far handling three aggregation attitudes towards uncertain information. In particular, based on Choquet integrals for belief measure, probability measure, and plausibility measure, CI$\_$bi/-, CI$\_$pr/ and CI$\_$pl/-aggregator are constructed, respectively. To illustrate a validity of proposed aggregation framework, multiple matching systems are developed by combining three simple individual template-matching systems and tested under various image variations. Finally, compared to individual matchers as well as other traditional multiple matchers in terms of an accuracy rate, it is shown that a proposed CI-aggregator system, {CI$\_$bl/-aggregator, CI$\_$pl/-aggregator, Cl$\_$pl/-aggregator}, is likely to offer a potential framework for either enhancing completeness or for resolving conflict or for reducing uncertainty of partial information.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1066-1070
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• 2003

Recently technologies have created new principle and theory but the PID control system remains its popularity as the PID controller contains simple structure, including maintenance and parameter adjustment being so simple. Thus, this paper proposes auto tune PID by fuzzy logic controller based on FPGA which to achieve real time and small size circuit board. The digital PID controller design to consist of analog to digital converter which use chip TDA8763AM/3 (10 bit high-speed low power ADC), digital to analog converter which use two chip DAC08 (8 bit digital to analog converters) and fuzzy logic tune digital PID processor embedded on chip FPGA XC2S50-5tq-144. The digital PID processor was designed by fundamental PID equation which architectures including multiplier, adder, subtracter and some other logic gate. The fuzzy logic tune digital PID was designed by look up table (LUT) method which data storage into ROM refer from trial and error process. The digital PID processor verified behavior by the application program ModelSimXE. The result of simulation when input is units step and vary controller gain ($K_p$, $K_i$ and $K_d$) are similarity with theory of PID and maximum execution time is 150 ns/action at frequency are 30 MHz. The fuzzy logic tune digital PID controller based on FPGA was verified by control model of level control system which can control level into model are correctly and rapidly. Finally, this design use small size circuit board and very faster than computer and microcontroller.

• International Journal of Quality Innovation
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• v.5 no.2
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• pp.45-62
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• 2004

Any business activities may have impact on environment to a certain extent. Enterprises must find appropriate approaches to measure the impact on these environmental aspects, which can be used as the basis to direct enterprises' efforts to improve the environmental impact. The method used to evaluate significant factors in life cycle assessment standards is the one most commonly used by enterprises in general to measure environmental impact. By this method, the decisive factors of each environmental aspect are given scores according to the preset scoring standard of the organization. The scores are added up for each aspect and ranked to assess major environmental aspects. The drawback of this assessment method, that is, it ignores the degree to which each of these factors affects the environment, results in poor credibility. Therefore, this study attempts to solve some qualitative problems by applying to fuzzy theory, in particular, by identifying appropriate fuzzy numbers through fuzzy sets and membership function. Moreover, the study seeks to obtain a crisp value in the process of defuzzifization in order to make up for the shortfall of the original method in dealing with relative weight of decisive factors and thus increase its applicability and credibility. The department of light production of an electronics company is used as an example in this study to measure environmental aspects by employing both the traditional significant factor method and the fuzzy environmental impact assessment model proposed in this study. Based on verification and comparison of results, the model proposed in this study is more feasible as it reduces partiality in decision-making by taking the relative weights of decisive factors into consideration.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.167-175
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• 2007

Fuzzy logic is used to represent qualitative knowledge and provides interpretability to a controlling system model in bioinformatics. This paper focuses on a bioinformatics data classification which is an important bioinformatics application. This paper reviews the two traditional controlling system models The sequence-based threshold controller have problems of optimal range decision for threshold readjustment and long processing time for optimal threshold induction. And the binary-based threshold controller does not guarantee for early system stability in the GPCR data classification for optimal threshold induction. To solve these problems, we proposes a fuzzy-based threshold controller for ART1 clustering in GPCR classification. We implement the proposed method and measure processing time by changing an induction recognition success rate and a classification threshold value. And, we compares the proposed method with the sequence-based threshold controller and the binary-based threshold controller The fuzzy-based threshold controller continuously readjusts threshold values with membership function of the previous recognition success rate. The fuzzy-based threshold controller keeps system stability and improves classification system efficiency in GPCR classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.593-597
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• 2004

This paper presents the new design method of fuzzy control system for nonlinear system. Many conventional design methods for fuzzy controller find the control gain for stabilizing fuzzy controller with some mathematical approaches. However, there exist some controllers which are hard to design with mathematical approach. In order to solve these problems, we propose the intelligent design method for fuzzy controller by using genetic algorithm with evolution strategy. The genetic algorithm with evolution strategy finds the control gain by changing the evolution region of chromosome. Finally, an application example of stabilizing a cart-pole typed inverted pendulum system will be given to show the stabilizability of the fuzzy controller.

• Computers and Concrete
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• v.2 no.4
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• pp.325-343
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• 2005

Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.