• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1378-1381
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• 1993

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.164-167
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• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.105-111
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• 1993

Human works shift its roll from physical condition to the system supervisory control task In this paper safety-presentation configuration is discussed instead of well-known fault-warning configuration. Of paticular interest was the personal factor which include the cognitive process. Through a performance between each person information processing(d') and decision process($\beta$) was pointed out to explain the sensitivity of personal cognitive process. Impact of uncertainty effect the supervisor having doubt situations. These facts are released by the use of flat fuzzy number of $\beta$ and its learning rate R.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.103-106
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• 1996

This paper presents an iterative fuzzy learning control scheme which is applicable to a broad class of nonlinear systems. The control scheme achieves system stability and boundedness by using the linear feedback plus adaptive fuzzy controller and achieves precise tracking by using the iterative learning rules. The switching mode control unit is added to the adaptive fuzzy controller in order to compensate for the error that has been inevitably introduced from the fuzzy approximation of the nonlinear part. It also obviates any supervisory control action in the adaptive fuzzy controller which normally requires high gain signal. The learning control algorithm obviates any output derivative terms which are vulnerable to noise.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.1-24
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• 2001

This paper present the idea that the inner loop regulator inside the servo can be enhanced its performance by replace the conventional control with a fuzzy proportional derivative control. In this paper, we replace an inner loop regulator of a Futaba servomotor with a fuzzy PD control paradigm. We then test the proposed system and compare the result with the original scheme. The fuzzy control used here is based on the supervisory scheme of the conventional PD yet embedded a fuzzy decision for the final control action. The proposed control scheme for the servomotor has shown robustness and effective performance in handle input disturbance along with its tracking ability. Moreover, when we embedded the new implemented on a real six-legged insect robot designed by the authors, we found that the control system for this application under the ...

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.5 s.45
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• pp.41-52
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• 2005

Using the variable control gain scheme on the basis of fuzzy-based decision-making process, Fuzzy supervisory control (FSC) technique exhibits better control performance than linear control technique with one static control gain. This paper demonstrates the effectiveness of the FSC technique by evaluating the robust performance of the FSC technique under the presence of uncertainties in the models and the excitations. Robust performance of the FSC system is compared with that of optimally designed LQG control system for the benchmark cable-stayed bridge presented by Dyke et al. Parameter studies on the robust performance evaluation are carried out by varying the stiffness of the bridge model as well as the magnitudes of several earthquakes with different frequency contents. From the comparative study of two control systems, FSC system shows the enhanced control performance against various magnitudes of several earthquakes while maintaining lower level of power required for controlling the bridge response. Especially, FSC system clearly guarantees the improved robust performance of the control system with stable reduction effects on the seismic responses and slight increases in total power and stroke for the control system, while LQG control system exhibits poor robust performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.398-403
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• 2009

The recent trend of logistics demands for improved monitoring system of the inside of containers including current temperature and other environmental conditions. This paper presents an information processing technique with fuzzy logic that recognizes the current situations inside the target container and can be implemented on intelligent container systems. The ZigBee modules are used to collect information such as temperature, humidity, and shock inside the container in ubiquitous environment. The information processing system using fuzzy logic and the InTouch, one of SCADA(Supervisory Control and Data Acquisition) systems, is implemented to monitor the inside of the container and predict the emergency state.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1727-1731
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• 2003

In this paper we proposed backward fuzzy Petri-net to diagnoses faults in power systems by using the time sequence information of protection system. As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. The fuzzy Petri-net models of protection system are composed of the operating process of protective devices and the fault diagnosis process. Fault diagnosis model, which makes use of the nature of fuzzy Petri-net, is developed to overcome the drawbacks of methods that depend on operator knowledge. The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method covers online processing of real-time data from SCADA (Supervisory Control and Data Acquisition)

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.390-394
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• 1994

A elevator group supervisory system is designed to perform efficient operation of multiple elevators, and its basic function is to assign an appropriate elevator to a given hall-cell. In this paper, in order to improve elevator group control performance, we propose a new dispatching system which includes fuzzy multi-attribute decision making(MADM). In most cases, the purpose of group control is to maximize control goals as much as possible. Unfortunately, the decision of optimal elevator to a given hall cell is made with very uncertain information of the system, and some of control goals are related each other. The uncertainty is mainly resulted from car calls generated by serving hall calls. A fuzzy MADM algorithm is proposed to deal with these problems to improve system performance.