• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1414-1417
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• 1993

Wang and Medel proved (1991) that fuzzy systems with product inference, centroid defuzzification, and everywhere positive membership functions (in particular, Gaussians, Wang, 1992) are capable of approximating any real continuous control function on a compact set to arbitrary accuracy. Kosko (1992) proved that fuzzy systems, in which membership functions have compact support, and combination operation (V-operation) for rules is the sum, are also universal approximators. In this paper, we generalize this result of Kosko and prove that for any &- and V-operations, any defuzzification procedure, and any basic membership function with a compact support, the resulting fuzzy controls are universal approximators. Also, Wang's result is transfered to min-inference.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2408-2410
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• 2001

This paper presents the control of an underactuated two-link robot called the Pendubot. Combining linearized state feedback control with Takagi-Sugeno(T-S) fuzzy controller wide-range stabilization of Pendulum is achieved. The local stabilization controler is designed by linearinzing the dynamic equations about the several desired set point and using LQR(Linear Quadratic Regulator) techniques. Takagi-Sugeno methodology is used to control the nonlinear models near different operation points. Fuzzy controller is obtained by the fuzzy blending of the local controllers. The paper includes a description of the algorithm as well as real time experimental results for the Pendubot.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.402-408
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• 2017

This paper deals with a robust ${\mathfrak{H}}_{\infty}$ controller design problem for waypoints tracking of large displacement unmanned underwater vehicles (LDUUVs) in Takagi-Sugeno fuzzy form. The LDUUV model uses a rudder to control its horizontal motion. We determine the order of waypoints based on their priorities and consider only surge force. A fuzzy controller in state-feedback form is taken and its design condition of is represented in terms of linear matrix inequalities. A numerical simulation is included to show the effectiveness of the theoretical development.

• Research in Mathematical Education
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• v.9 no.3 s.23
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• pp.233-241
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• 2005

Mathematics has developed dramatically in today's world and come to be increasingly put into practical use in various fields in society. However, many Japanese students dislike mathematics. We have to study mathematics education with this situation in our mind. When we consider a better educational material, we don't have to consider only within the framework of the current school mathematics. We can expect to find good mathematical materials in fields beyond the school mathematics. In this paper, we study how the inclusion of idea such as 'fuzzy theory' and 'graph theory' influences pupils' approaches to learning mathematics.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1362-1365
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• 1993

Fuzzy mathematics is used to elicit and evaluate human psychophysical responses in panel tests. The fundamental instrument used is a bar graph whose data is then converted to a paired comparison matrix. Form this matrix we use the theory of Perron and Froebenius to obtain an eigenvalue and eigenvector which indicates not only the panelist's comparitive responses but also the consistency of the responses from that panelist. Tests were done to evaluate the procedure.

• Journal of Power Electronics
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• v.15 no.3
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• pp.730-740
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• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.15-24
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• 2000

This paper presents an output feedback robust H$\infty$ control problem for a class of uncertain nonlinear systems, which can be represented by an fuzzy dynamic model. The nonlinear system is represented by Takagi-Sugeno fuzzy model, and the control design is carried out on the basis of the fuzzy model. Using a single quadratic Lyapunov function, the globally exponential stability and disturance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H$\infty$ controllers are given in terms of linear matrix inequalities(LMIs). Constructive algorithm for design of robust H$\infty$ controller is also developed. The resulting controller is nonlinear and automatically tuned based on fuzzy operation.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.3
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• pp.240-248
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• 1999

This paper presents the application of fuzzy algorithm for speed control of Switched Reluctance Motor. SRM has a h highly nonlinear control characteristic and operates in saturation to maximize the motor torque. A systematic approach t to the modeling of highly nonlinear SRM drive system which includes the fuzzy controller with coarse control and fine C control is presented. PelfOlmance analysis of SRM dJive is reported for a wide range of operating conditions through s speed variation and load perturbation dynamics. The pelfOlmance indices of SRM drive system operating with fuzzy 1 logic controller are compared with the conventional controller to highlight the merits. The expel1mental results are p presented to confilm the validity of proposed fuzzy 10밍c controller.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.851-859
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• 2021

Small PWR can be used for power generation and heating. Considering that small PWR has the characteristics of flexible operating conditions and complex operating environment, the controller designed based on single power level is difficult to achieve the ideal control of small PWR in the whole range of core power range. To solve this problem, a flexible switching controller based on fuzzy controller and LQG/LTR controller is designed. Firstly, a core fuzzy multi-model suitable for full power range is established. Then, T-S fuzzy rules are designed to realize the flexible switching between fuzzy controller and LQG/LTR controller. Finally, based on the core power feedback principle, the core flexible switching control system of small PWR is established and simulated. The results show that the flexible switching controller can effectively control the core power of small PWR and the control effect has the advantages of both fuzzy controller and LQG/LTR controller.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.197-199
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• 2000

The various criteria to identify the disturbances of the power transformer has been reported in this paper. They have been derived through EMTP simulations of internal faults, inrush and overexcitation for the model of 154/22.9[kV], 40[MVA], Y-Y three-phase power transformer. We also propose the algorithm which makes bpa Functions and infers the final decision from them based on Modfied Dempster-Shafer's rule of combination.