• Journal of Industrial Technology
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• v.30 no.A
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• pp.111-117
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• 2010

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.907-910
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• 1993

This paper describes the use of fuzzy control and decision making to simulate the control of traffic flow at an intersection. To show the value of fuzzy logic as an alternative method for control of traffic environments. A traffic environment includes the lanes to and from an intersection, the intersection, vehicle traffic, and signal lights in the intersection. To test the fuzzy logic controller, a computer simulation was constructed to model a traffic environment. A typical cross intersection was chosen for the traffic environment, and the performance of the fuzzy logic controller was compared with the performance of two different types of conventional control. In the hardware verifications, fuzzy logic was used to control acceleration of a model train on a circular path. For the software experiment, the fuzzy logic controller proved better than conventional control methods, especially in the case of highly uneven traffic flow between different directions. On the hardware si e of the research, the fuzzy acceleration control system showed a marked improvement in smoothness of ride over crisp control.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.48-57
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• 1997

This paper presents the automatic construction and parameter optimization technique for fuzzy logic controllers using genetic algorithm. In general. the design of fuzzy logic controllers has difficulties in the acq~lisition of expert's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controllers c:an be degraded in the case of plant parameter variations or unpredictable incident which a designer may have ignored, and the parameters of fuzzy logic controllers obtained by expert's control action may not be optirnal. Some of these problems can be resolved by the use of genetic algorithm. The proposed method can tune the parameters of fuzzy logic controllers including scaling factors and determine: the appropriate number of fuzzy rulcs systematically. Finally, we provides the second order dead time plant to evaluate the feasibility and generality of the proposed method. Comparison shows that the proposed method can produce fuzzy logic controllers with higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controllers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.318-322
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• 2016

A quad-copter or quad rotor system is an unmanned flying machine having four engines, which their thrust force is produced by four propellers. Its stable control is very important and has widely been studied. It is a typical example of a nonlinear system. So, it is difficult to get a desired control performance by conventional control algorithms. In this paper, we propose the design of a vectored sum defuzzification based fuzzy logic system for the hovering control of a quad-copter. We first summarize its dynamics and introduce a vectored sum defuzzification scheme. And then we design a vectored sum defuzzification based fuzzy logic system. for the hovering control of the quad-copter. Finally, in order to check the feasibility of the proposed system we present some simulation examples.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.100-108
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• 2002

A fuzzy logic for collision avoiding navigation of marine vehicles is proposed in this paper. VFF(Virtual Force Field) method, which is used widely in the field of mobile robots, is modifiel to apply to marine vehicles. The method is named MVFF (Modified Virtual Force Field) mothod. The MVFF consists of the determination of the heading angles far track-keeping mode ($\psi_{ca}$)and collision avoidance mode ($\psi_{ca}$). The operator can choose the pattern of the track-keeping mode in the proposed algorithm. The collision avoidance algorithm can handle static and/or moving obstacles. These functons are implemented using fuzzy logic. Various simulation results verify the proposed alogorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.138-145
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• 1998

Recently, TCS(Traction Control System) is attracting attention, because it maintains traction ability and steerability of vehicles on low-$\mu$ surface roads by controlling the slip rate between tire and road surface. The development of TCS control law is difficult due to the highly nonlinearity and uncertainty involved in TCS. A fuzzy logic approach is appealing for TCS. In this paper, fuzzy logic controller for TCS is introduced and evaluated by the computer simulation with 8 DOF vehicle model. The result indicate that the fuzzy logic TCS improves vehicle's stability and steerability.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.514-519
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• 2001

This Paper presents an application of a on-line self-organizing fuzzy logic controller to a boiler system of fossil-power plant. A boiler-turbine system is described as a MIMO nonlinear system in this paper. Then, three single loop fuzzy logic controllers are designed independently. The control rules and the membership functions of proposed fuzzy logic control system are generated automatically without using plant model. The simulation shows successful results for wide range operation of boiler system of fossil-power plant.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.174-176
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• 2003

This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.