• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.179-184
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• 2002

Recently, internet-based applications can be found easily in various felds. Internet-based telerobot system becomes one of important applications of internet. Among many important technological issues on the internet-based telerobot, time-delay is inherently critical problem to be solved. Time-delay is classified as micro time-delay and macro time-delay in this paper. Algorithms for compensation of path-error and time-error are proposed for the both types of time-delays using fuzzy logic since fuzzy logic is one of the best tools to represent expert's knowledge. Simulation results show the validity of the proposed algorithms.

• 한국정밀공학회지
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• 제15권10호
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• pp.180-192
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• 1998

This paper introduces a new self-organizing fuzzy logic controller (SOFLC) for precision contour machining in the presence of large disturbances which adjusts both input and output membership functions simultaneously. The parameters of the proposed controller are self-tuned in real-time according to a continuous measurement of the performance of the controller itself and estimated disturbance values. The proposed controller as well as a conventional fuzzy logic controller and a PID controller were simulated and implemented on a 3-axis milling machine in contour milling. Both the simulations and experiments show that the self-organizing fuzzy logic controller has superior performance in terms of contour tracking accuracy compared with the other two controllers.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2005년도 춘계학술대회 논문집
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• pp.5-9
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• 2005

One of the imminent problems to be solved within wireless sensor network is to balance out energy dissipation among deployed sensor nodes. In this paper, we present a transmission relay method of communications between BS (Base Station) and CHs (Cluster Heads) for balancing the energy consumption and extending the average lifetime of sensor nodes by the fuzzy logic application. The proposed method is designed based on LEACH protocol. The area deployed by sensor nodes is divided into two groups based on distance from BS to the nodes. RCH (Relay Cluster Head) relays transmissions from CH to BS if the CH is in the area far away from BS in order to reduce the energy consumption. RCH decides whether to relay the transmissions based on the threshold distance value that is obtained as a output of fuzzy logic system. Our simulation result shows that the application of fuzzy logic Provides the better balancing of energy depletion and Prolonged lifetime of the nodes.

• 대한기계학회논문집A
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• 제25권4호
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• pp.748-755
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• 2001

This paper concerns rotor vibration reduction using magnetic damper system. The fuzzy control logic is utilized to fulfill desired motion. The fuzzy system structure and membership function were first determined by simulation results. The researched control logic contains two fuzzy controller : reference position variation according to the rotor whirling status and error compensation algorithm to minimize the rotor vibration due to unbalance and unstable fluid film force. The Sugeno type output membership function was utilized by several trials and optimized membership function constants were selected from experiments. The experimental results show that the proposed method effectively control and reduce the rotor vibration with fluid film bearings.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 추계학술대회 논문집
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• pp.69-72
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• 2003

The paper presents implementation of a PV fuzzy logic power tracking controller. Using maximum power point tracker with the intermediate converter can increase the system efficiency by matching the PV system to the load. A new fuzzy MPPT is proposed, where fuzzy inputs parameters are dp/dI and the last incremental of duty of duty ratio $L{\delta}D$, and the output is the new incremental value $(new{\delta}D)$ according to the maximum power point under various illumination levels.

• Structural Engineering and Mechanics
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• 제37권4호
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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.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(2)
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• pp.503-506
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• 2003

The photovoltaic generators have a nonlinear V-I characteristics and maximum power points which vary with the illumination levels and temperatures. Using maximum power point tracker with the intermediate converter can increase the system efficiency by matching the PV systems to the load. A novel MPPT control for photovoltaic system is proposed. The system input parameters are (dP, dI, and last incremental of duty ratio $L\deltaD$)and the output is the new incremental value (new ${\deltaD}$) according to the maximum power point under various illumination levels. Using fuzzy logic controller allows extracting the maximum power rapidly and without significant oscillations. Also FLC provides excellent features such as fast response, good performance and the ability to change the fuzzy parameters to improve control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4987-5005
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• 2017

This paper introduces a new method to solve Similarity Recognition for Cloth Products, which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience, it is called the SRCPFP method hereafter. In this paper, the SRCPFP method combines Fuzzy Logic (FL) and Particle Swarm Optimization (PSO) algorithm to solve similarity recognition for cloth products. First, it establishes three features, length, thickness, and temperature resistance, respectively, for each cloth product. Subsequently, these three features are engaged to construct a Fuzzy Inference System (FIS) which can find out the similarity between a query cloth and each sampling cloth in the cloth database D. At the same time, the FIS integrated with the PSO algorithm can effectively search for near optimal parameters of membership functions in eight fuzzy rules of the FIS for the above similarities. Finally, experimental results represent that the SRCPFP method can realize a satisfying recognition performance and outperform other well-known methods for similarity recognition under considerations here.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.7-12
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• 2003

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.