• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.228-236
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• 2004

In this paper. we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feed forward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand. feed forward neural networks provide salient features. such as learning and parallelism. In the proposed neuro-fuzzy controller. the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error back propagation algorithm as a learning rule. while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally. the effectiveness of the proposed controller is verified through computer simulation for an inverted pole system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.518-522
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• 2002

This paper proposes a new application of Fuzzy logic to Variable Step Size Least Mean Square (VS-LMS) adaptive beamforming algorithm in CDMA systems. The proposed algorithm adjusts the step size of the Least Mean Square (LMS) by using the application of Fuzzy logic in which the increase or decrease of step size depends on the fuzzy inference results of the Mean Square Error (MSE). Computer simulation results show that the proposed algorithm has a better capacity of tracking compared with the conventional LMS algorithms and other variable step size LMS algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1066-1070
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• 2003

Recently technologies have created new principle and theory but the PID control system remains its popularity as the PID controller contains simple structure, including maintenance and parameter adjustment being so simple. Thus, this paper proposes auto tune PID by fuzzy logic controller based on FPGA which to achieve real time and small size circuit board. The digital PID controller design to consist of analog to digital converter which use chip TDA8763AM/3 (10 bit high-speed low power ADC), digital to analog converter which use two chip DAC08 (8 bit digital to analog converters) and fuzzy logic tune digital PID processor embedded on chip FPGA XC2S50-5tq-144. The digital PID processor was designed by fundamental PID equation which architectures including multiplier, adder, subtracter and some other logic gate. The fuzzy logic tune digital PID was designed by look up table (LUT) method which data storage into ROM refer from trial and error process. The digital PID processor verified behavior by the application program ModelSimXE. The result of simulation when input is units step and vary controller gain ($K_p$, $K_i$ and $K_d$) are similarity with theory of PID and maximum execution time is 150 ns/action at frequency are 30 MHz. The fuzzy logic tune digital PID controller based on FPGA was verified by control model of level control system which can control level into model are correctly and rapidly. Finally, this design use small size circuit board and very faster than computer and microcontroller.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.351-365
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• 2011

This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.12-18
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• 2011

This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose a new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.1999-2001
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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 Control, Automation, and Systems
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• v.2 no.2
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• pp.171-181
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• 2004

An autonomous navigation algorithm for marine vehicles is proposed in this paper using fuzzy logic under COLREG guidelines. The VFF (Virtual Force Field) method, which is widely used in the field of mobile robotics, is modified for application to the autonomous navigation of marine vehicles. This Modified Virtual Force Field (MVFF) method can be used in either track-keeping or collision avoidance modes. Moreover, the operator can select a track-keeping pattern mode in the proposed algorithm. The collision avoidance algorithm has the ability to handle static and/or moving obstacles. The fuzzy expert rules are designed deliberately under COLREG guidelines. An extensive simulation study is used to verify the proposed method.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.206-208
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• 1997

This paper presents a design of self_tuning fuzzy logic controller using Genetic Algorithms for power system stabilization. FPSS(Fuzzy Logic Power System Stabilized is applied to the KERI(Korea Electric Research Int.) power system simulator so that its efficiency can be investigated in real time control. Genetic Algorithms are used to determine fuzzy membership functions. Experiment results show the better performances with FPSS in comparison to no PSS.

• 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.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.91-91
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• 1998