• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1078-1081
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• 1993

The Objective of this paper is to provide fuzzy control designers with a design tool for stable fuzzy logic controllers. Given multiple sets of data disturbed by vagueness uncertainty, we generate the implicative rules that guarantee stability and robustness of closed-loop fuzzy dynamic systems. We propose the cell-state transition method which utilizes Hsu's cell-to-cell mapping concept [1]. As a result, a generic and implementable design methodology for obtaining a fuzzy feedback gain K, a fuzzy hypercube [2], is provided and illustrated with simple examples.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.651-658
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• 2007

This paper presents a new type of fuzzy logic-based power control strategy for fuel cell hybrid electric vehicles designed to improve their fuel economy while maintaining the battery's state of charge. Since fuel cell systems have inherent limitations, such as a slow response time and low fuel efficiency, especially in the low power region, a battery system is typically used to assist them. To maximize the advantages of this hybrid type of configuration, a power distribution control strategy is required for the two power sources: the fuel cell system and the battery system. The required fuel cell power is procured using fuzzy rules based on the vehicle driving status and the battery status. In order to show the validity and effectiveness of the proposed power control strategy, simulations are performed using a mid-size vehicle for three types of standard drive cycle. First, the fuzzy logic-based power control strategy is shown to improves the fuel economy compared with the static power control strategy. Second, the robustness of the proposed power control strategy is verified against several variations in system parameters.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1058-1062
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• 1993

A fuzzy reasoning method is proposed for the implementation of control systems based on non-fuzzy microprocessors. The essence of the proposed method is to search the local active miles instead of the global rule base. Thus the reasoning is conveniently performed on a master cell as a fuzzy accelerating kernel, which is transformed from an active fuzzy cell. The interpolative reasoning is simplified via adopting the algebraic product of fulfillment for the conditional connective AND and the weighted average for the rule sentence connective ALSO.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.305-310
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• 1997

In this paper, a fuzzy set based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy logic is emoloyed to express the degree of appropriateness when alternative machines are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.388-388
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• 2000

The complexity of nonlinear systems makes it difficult to ascertain their behavior using classical methods of analysis. Many efforts have been focused on the advanced algorithms and techniques that hold the promise of improving real-time optimal control while at the same time providing higher accuracy. In this paper, a fuzzy cell mapping method of real-time optimal control far nonlinear dynamical systems is proposed. This approach combines fuzzy logic with cell mapping techniques in order to find the optimal input level and optimal time interval in the finite set which change the state of a system to achieve a desired obiective. In order to illustrate this method, we analyze the behavior of an inverted pendulum using fuzzy cell mapping.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.987-992
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• 1998

Solar cell has an optimum operating point to extract maximum power. To control operating point of the solar cell, a fuzzy controller has already been proposed by our research group. However, several parameters are determined by trial and error. To overcome this problem, this paper adopts Fuzzy Neural Network (FNN) for maximum power point tracking control for photovoltaic array. The FNN can be trained to perfect fuzzy rules and to find an optimum membership functions on-line.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.2
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• pp.99-104
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• 2011

In this paper, the intelligent landscape lighting power control and monitoring system with solar sell generator equipment is proposed. The first, the intelligent landscape lighting power controller is designed using the fuzzy logic control method. And the fuzzy logic controller is used to save power consumption for various reference intensity of the illumination. The second, the GUI monitoring system is presented. It has control and display faculty. And the practical experiment device is used to evaluate the performance criteria of the proposed intelligent landscape lighting power control system with the solar cell power generation equipment. From the experiment results, we present the property of proposed fuzzy controller such as steady state error, the tracking and power consumption characteristic for the reference intensity of illumination. And also we show the superiority of power control as well as the characteristic of GUI monitoring system in the proposed system.

• Transactions of the Korean hydrogen and new energy society
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• v.28 no.4
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• pp.369-376
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• 2017

Temperature and humidity regulations of an open-cathode PEM fuel cell with balance of plant (BOP) are developed in this study. The axial fan, a bubble humidifier, set of solenoid valves and a controller are used to perform temperature and humidity control simultaneously. A fuzzy controller is designed, and it shows its superiority in real-time controlling for strong non-linear dynamical fuel cell system. The axial fan speed is used for temperature control and solenoid valve on/off signal of the bubble humidifier is used for humidity control. The axial fan speed is controlled to keep the fuel cell temperature within the desired point. Meanwhile, the bubble humidifier is utilized to moisture hydrogen to manage the water content of membrane. The results show that the proposed fuzzy controller effectively increases the output power of 10% for a PEM fuel cell.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1033-1036
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• 1993

Most of the today realized fuzzy logic control applications has been designed using different heuristic approaches for synthesis and implemented with conventional programming languages on general purpose microcontrollers. This paper aims to present a new methodology to design a fuzzy controller. The methodology is based on the Cell-to-Cell approach to extract the control law. A set of fuzzy rules is then found by using a FAM (Fuzzy associative memories) approach. The proposed procedure was implemented to control the rotor position of a DC motor.