• Journal of Power Electronics
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• 제4권3호
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• pp.127-137
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• 2004

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of an unconstrained optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.

• 한국지능시스템학회논문지
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• 제18권2호
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• pp.236-242
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• 2008

본 논문은 회전형 역 진자 시스템(Rotary Inverted Pendulum System : RIPS)에 대한 계층적 공정 경쟁 기반 유전자 알고리즘(Hierarchical Fair Competition-based Genetic Algorithms : HFCGA) 기반 최적 퍼지 제어기 설계를 제안한다. 회전형 역 진자 시스템의 제어를 위해 퍼지제어기를 사용하였으며, 이때 퍼지제어기의 규칙은 LQR(Linear Quadratic Regulator) 제어기를 기반으로 하여 설계하였다. 유전자 알고리즘은 전역해를 구할 수 있는 장점이 있어 많은 분야에 성공적으로 적용되고 있지만 조기수렴 문제로 인하여 지역해에 빠질 수 있다. 이러한 문제를 해결하기 위하여 병렬유전자 알고리즘이 개발되었으며, HFCGA는 병렬유전자 알고리즘을 개선한 방법 중의 하나이다. 본 논문에서는 퍼지 제어기의 파라미터의 최적화를 위해 계층적 공정 경쟁 기반 유전자 알고리즘을 사용하였다. 시뮬레이션 및 실험을 통하여 LQR 제어기, 기존 단순유전자 알고리즘(SGA)을 이용한 퍼지제어기와 제안된 HFCGA 기반 퍼지제어기의 성능 비교를 통하여 제안된 방법의 우수성을 보인다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.413-417
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• 2004

This paper proposes a fuzzy proportional-Integral (PI) controller for the precise tracking control of optical disk systems based on the genetic algorithm (GA). The fuzzy PI control rules are optimized by the GA to yield an optimal fuzzy PI controller. We validate the feasibility of the proposed method through a numerical simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.509-511
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• 1998

Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership function and fuzzy rule base, which is traditionally achieved by tedious trial-and-error process. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm(GA). The controller design space is coded in base-7 strings chromosomes, where each bit gene matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a do-servo motor control system. It was presented in discrete fuzzy linguistic value, and used a membership function with Gaussian curve. The performance of this control system is demonstrated higher than that of a conventional PID controller and fuzzy logic controller(FLC).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.735-738
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• 1997

The traffic congestion caused by the exploding increase of vehicles became one of the severest social problems. Among the various approaches to solve this problem, controlling the length of traffic signals appropriately according to the individual traffic situation would be the most plausible and cost-effective method. To design a traffic signal controller which has such a property as adaptive decision-making process, we adopt fuzzy logic control method(fuzzy traffic signal controller), Moreover, using genetic algorithms we obtain an optimized fuzzy traffic signal controller (GA-fuzzy traffic signal controller). To evaluate and validate the proposed fuzzy and GA-fuzzy traffic signal controller, simulation results are presented.

• Journal of Advanced Marine Engineering and Technology
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• 제29권2호
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• pp.225-235
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• 2005

In this Paper, it was designed the GA-fuzzy controller of a Thyristor Controlled Series Capacitor(TCSC) for enhancement of power system stability. The newly designed controller of TCSC was designed to overcome the nonlinearity such as operating point change of power system as well as to respond to disturbances as uncertainties of line parameters and line fault. So, fuzzy controller by intelligent control theory was used for it. And the fuzzy controller was optimized from a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller namely. scaling factor. membership function and control rules. Nonlinear simulation results show that the proposed control technique is superior to conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2666-2668
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• 2001

Fuzzy system which are based on membership functions and rules, can control nonlinear, uncertian, complex system well. However, Fuzzy controller has problems: It is difficult to design a stable for amateur. To update the then-part membership functions of the fuzzy controller can be designed using the Optimal fuzzy controller. Then we could be optimized the system choosing a good performance index. The proposed fuzzy controller based on Optimal fuzzy control is an Truck-Backer for demonstration of the robustness of proposed methodology.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 F
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• pp.2742-2744
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• 1999

In this paper, an auto-tuning method for fuzzy logic controller based on the genetic algorithm is presented. In the proposed method, normalization parameters and membership function parameters of fuzzy controller are translated into binary bit-strings, which are processed by the genetic algorithm in order to be optimized for the well-chosen objective function (i.e. fitness function). To examine the validity of the proposed method. a genetic algorithm based fuzzy controller for an indirect vector control of induction motors is simulated and experiment is carried out. The simulation and experimental results show a significant enhancement in shortening development time and improving system performance over a traditional manually tuned fuzzy logic controller.

• 유공압시스템학회논문집
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• 제2권4호
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• pp.1-6
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• 2005

This paper presents optimization of a pneumatic control system whose design parameters have been optimized so that the desired dynamic characteristics of cylinder position was obtained. The pneumatic system is used as transferring and stacking equipment for solid freeform fabrication system which has been widely used in design verification applications. The pneumatic system mainly consists of pneumatic control valves and cylinders. The system was modeled by using several principles for pneumatic components. The system was optimized to obtain dynamic performance with enough damping to reduce cylinder vibration. A fuzzy controller has been applied to fulfill the dynamic performance requirements of the pneumatic system. The simulation results show that the fuzzy controller is more effective than a PD controller.

• 한국조명전기설비학회지:조명전기설비
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• 제13권2호
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• pp.195-195
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• 1999

This paper is Proposed a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. So we can find the parameters of PID controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of PID controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of PID controller is found by Neural-Network Program.