• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1998.11a
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• pp.181-185
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• 1998

A speed controller of a induction motor using Microcontroller and Fuzzy logic is presented in the paper. Generally, fuzzy logic controller is known as a controller which can be coped with a non-linear and a complex system. A fuzzy logic is used for robust and fast speed control and space vector modulation method is used for PWM wave generation in this proposed system. The results of experiment show excellence of the proposed system and that the proposed system is appropriate to control the speed of a induction motor for industrial application.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

• 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.11
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• pp.3665-3674
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• 2021

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.211-213
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• 1993

In this paper, we proposed a design method of self-learning fuzzy logic controller using fuzzy neural network. The parameters of membership function in premise are modified by descent method and also consequent parameters by learning mechanism of animal conditioning theory. The proposed method is applied to pole balancing system in order to confirm the feasibility.

• Smart Structures and Systems
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• v.13 no.3
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• pp.473-500
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• 2014

Tuned mass dampers (TMDs) have been installed in many high-rise buildings, to improve their resiliency under dynamic loads. However, high-rise buildings may experience natural frequency changes under ambient temperature fluctuations, extreme wind loads and relative humidity variations. This makes the design of a TMD challenging and may lead to a detuned scenario, which can reduce significantly the performance. To alleviate this problem, the current paper presents a proposed approach for the design of a robust and efficient TMD. The approach accounts for the uncertain natural frequency, the optimization objective and the input excitation. The study shows that robust design parameters can be different from the optimal parameters. Nevertheless, predetermined optimal parameters are useful to attain design robustness. A case study of a high-rise building is executed. The TMD designed with the proposed approach showed its robustness and effectiveness in reducing the responses of high-rise buildings under multidirectional wind. The case study represents an engineered design that is instructive. The results show that shear buildings may be controlled with less effort than cantilever buildings. Structural control performance in high-rise buildings may depend on the shape of the building, hence the flow patterns, as well as the wind direction angle. To further increase the performance of the robust TMD in one lateral direction, active control using LQG and fuzzy logic controllers was carried out. The performance of the controllers is remarkable in enhancing the response reduction. In addition, the fuzzy logic controller may be more robust than the LQG controller.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.624-629
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• 1998

Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.994-997
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• 2003

This Paper presents a study of the performance of a DC servo motor with a model reference adaptive fuzzy speed controller (MRAFSC) in the presences of load disturbances. MRAFSC comprised inner feedback loop consisting of the fuzzy logic controller (FLC) and plant, and outer loop consisting of an adaptation mechanism which is designed for tuning a control rule of the FLC. Experimental results show the good performance in the DC servo motor system with the proposed adaptive fuzzy controller.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.66-78
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• 2009

This paper introduces the design of a fuzzy logic controller in conjunction with direct torque control strategy for a Permanent Magnet synchronous machine. A stator flux angle mapping technique is proposed to reduce significantly the size of the rule base to a great extent so that the fuzzy reasoning speed increases. Also, a fuzzy resistance estimator is developed to estimate the change in the stator resistance. The change in the steady state value of stator current for a constant torque and flux reference is used to change the value of stator resistance used by the controller to match the machine resistance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2108-2111
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• 2005

The mission life of a satellite determines the amount of fuel required on-board, while the total mass requirement limits the fuel to be loaded. Hence, for the design of thruster control loop, not only the satellite pointing accuracy but the saving of fuel is to be considered. In this paper, a two-step fuzzy controller is proposed for the thruster control loop to save fuel consumption. This approach combines requirements for pointing control accuracy with minimum fuel consumption into a fuzzy controller design. To demonstrate this approach, we have designed a fuzzy controller for the Sun point Mode of KOMPSAT-2. The performance of this fuzzy controller design is compared with that of PD controller used for KOMPSAT-2.