• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.70.1-70
• /
• 2002

In the fuzzy applications and theories, it is very important to consider how to design the optimal fuzzy model from short training data, in order to construct the reasonable fuzzy model for identifying the practical process. There are several concerns to be confirmed for efficient fuzzy model design. One of concern is the optimization problem of the fuzzy model. In various applications, the genetic algorithm is widely applied to obtain optimal fuzzy model and other cases that adopt evolutionary mechanism of the nature. If we use natural selection and multiplication operation of the genetic algorithm, early convergence to local minimum can be occurred. In other word, we can find only optimum...

• Journal of information and communication convergence engineering
• /
• v.8 no.6
• /
• pp.702-708
• /
• 2010

This paper proposes a novel linearization method for Takagi.sugeno (TS) fuzzy model. A T-S fuzzy controller consists of linear controllers based on local linear models and the local linear controllers cannot be designed independently because of overall stability conditions which are usually conservative. To use linear control theories easily for T-S fuzzy system, the linearization of T-S fuzzy model is required. However, The linearization of T-S fuzzy model is difficult to be achieved by using existing linearization methods because fuzzy rules and membership functions are included in T-S fuzzy models. So, a new linearization method is proposed for the T-S fuzzy system based on the idea of T-S fuzzy state transformation. For the T-S fuzzy system linearized with uncertainties, a robust optimal controller with the robustness of sliding model control(SMC) is designed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.4
• /
• pp.526-533
• /
• 2007

In this paper, we study to the pattern of job satisfaction using four theories of transactional analysis-egogram, life positions, strokes, time structuring-for organizational members. The tool of pattern analysis is used fuzzy TAM network which Is especially effective for pattern analysis. The input data of fuzzy TAM network ate values of four theories in transactional analysis, the output data is the classes which is divided by two groups from score of job satisfaction. From the result of this study, the correct rates of training data and checking data are 85-100% and 60%, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.701-706
• /
• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.825-829
• /
• 2005

This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

• KIEE International Transactions on Power Engineering
• /
• v.2A no.3
• /
• pp.95-101
• /
• 2002

This paper illustrates a new fuzzy effective load model for probabilistic and fuzzy production cost simulation of the load point of the composite power system. A model for reliability evaluation of a transmission system using the fuzzy set theory is proposed for considering the flexibility or ambiguity of capacity limitation and overload of transmission lines, which are subjective matter characteristics. A conventional probabilistic approach was also used to model the uncertainties related to the objective matters for forced outage rates of generators and transmission lines in the new model. The methodology is formulated in order to consider the flexibility or ambiguity of load forecasting as well as capacity limitation and overload of transmission lines. It is expected that the Fuzzy CMELDC (CoMposite power system Effective Load Duration Curve) proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems in a competitive environment in the future. The characteristics of this new model are illustrated by some case studies of a very simple test system.

• Proceedings of the KIEE Conference
• /
• 2005.07d
• /
• pp.2671-2674
• /
• 2005

Auto Pilot System is the device for course keeping or course altering to ship's steering system. The purpose of automatic steering system is to keep the ship's course stable with the minimum course and rudder angle. Recently, modem control theories are being used widely in analyzing and designing the ship system. Though P.I.D type auto pilots are widely used in ships, the stability and the adjusting meyhods are not clarified. In this paper the authors proposed auto pilot system with Fuzzy Logic Controller. In the fuzzy control the things that the actual operators of a steering wheel has acquired through their experience can be logically described by the Lingustic Control Rule. The characteristic of the control system were investi gated through the computer simulation results. it was found that the fuzzy logic control was more efficient than the conventional system.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.880-886
• /
• 1992

There has been continuous effort to achieve total automation of the power plants. But due to complexity, nonlinearities and time-varying properties of the system, no success has been reported if conventional and/or modern control theories are applied. In spite of this, the start-up and shutdown operations are successfully performed by skilled human operators who are able to utilize a great wealth of knowledge and past experiences. In this paper, in order to automate the shutdown operation of power plants, it is proposed that the operation be performed by a more efficient method than the current used, through dividing the total process into several subprocesses, introducing checkpoints, and using fuzzy logic. For this, fuzzy logic controllers and fuzzy decision-makers are designed and the validity is shown by simulation via a set of piecewise continuous shutdown models.

• Journal of Korean Institute of Industrial Engineers
• /
• v.23 no.1
• /
• pp.39-54
• /
• 1997

This paper presents four process models for machining processes : 1) an economical mathematical model of machining process, 2) a prediction model for surface roughness, 3) a decision model for fuzzy cutting conditions, and 4) a judgment model of machinability with automatic selection of cutting conditions. Each model was developed the economic machining, and these models were applied to theories widely studied in industrial engineering which are nonlinear programming, computer simulation, fuzzy theory, and neural networks. The results of this paper emphasize the human oriented domain of a nonlinear programming problem. From a viewpoint of the decision maker, fuzzy nonlinear programming modeling seems to be apparently more flexible, more acceptable, and more reliable for uncertain, ill-defined, and vague problem situations.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.7
• /
• pp.3245-3250
• /
• 2011

This study introduces a threat level assessment model adapting Fuzzy theories in order to help make decisions for better covering quantitative factors and qualitative ones together. The threat is classified into three major categories - one resulting from navigational condition, another from target vessel specification and the other from external decision environment. The threat levels by each category are examined by a fuzzy inference, and its corresponding weights are assigned via fuzzy measures. Finally the high level threat measures become integrated via a Choquet Fuzzy Integral method into ultimate threat level indicators.