• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.488-493
• /
• 2008

A mathematical model of molten steel level for continuous casting process is presented, where the molten steel level, input and output flow in the mold, the relation between stopper position and input flow etc. are considered. The mathematical model is implemented and simulated by using MATLAB. Comparing the result of molten steel level from the simulator with that of real plant, the performance of the model is shown to be reasonable. By using this simulator, it is shown that PI controller with variable P gain, adjusted by fuzzy logic system, has better control result than conventional PI controller.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1994.10a
• /
• pp.12-12
• /
• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1161-1163
• /
• 1996

In this paper, a simulator is designed along with S/W package for crane controllers. Due to trolley's acceleration or deceleration, cranes inherently cause swing motion of the objects in transporting heavy objects. This swing not only deteriorates the crane handling safety but also increases the processing time. To overcome these drawbacks, the fuzzy rule-based simulator is developed with inhibitory swing at final action. The computer simulation shows that the swing at initial and final positions is removed fast with small position error. The proposed simulator can be used for handling object stablely and the study of effectiveness in unmanned operation of cranes.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.9 s.351
• /
• pp.142-148
• /
• 2006

Considering the domestic traffic environment and the increase of traffic accidents, we have been asked to exactly analyze the main causes of accidents for the accident-experienced drivers to be rehabilitated. In this thesis we present the development process and results of a driving simulator using the IPDE method in the interest of safe driving and driving rehabilitation. Through this Driving simulation development the rehabilitated driver has the possibility of experiencing the real driving situation with the driving aptitude and examines the reasons of accidents. Through the examinations the driver has the chance to correct the deformities of driving by choosing the explanatory scenes, and through this process the driver is able to develop the capability to react in the real situation. However this driving simulation system is one of the best developed, depending on weather and road condition the braking distance may change. Therefore the fuzzy rule and neural network have been used in this thesis to solve previously mentioned problem. The simulation exactly calculated the road and weather conditions to adjust the breaking intensity.

• Journal of Navigation and Port Research
• /
• v.33 no.1
• /
• pp.43-50
• /
• 2009

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out of them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability of casualty. In this study, the risk of collision and grounding is evaluated by two kinds of method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk of collision and grounding is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1994.04a
• /
• pp.55-67
• /
• 1994

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics ar low speed. In this paper the authors propose a new berthing control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's decision-making by using the FNN(Fuzzy neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS90 MK III) and represent the ship motion characteristics internally According to learning procedure both FNN controllers can tune membership functions and identify fuzzy control rules automatically The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.438-442
• /
• 1998

The helicopter system is non-linear and complex. Futhermore, because of absence of an accurate mathematical model, it is difficult accurately to control its attitude. But we can control the non-modeled system with the uncertainty and unstructure using the fuzzy control algorithm. Therefore, we apply optimized fuzzy controllers for the control of its elevation angle and azimuth one using expert's intuitions and knowledges. The simulation and experimental results of the hellicopter simulator CE150 with MATLAB shall be introduced.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.5
• /
• pp.435-442
• /
• 1997

The roof crane system is used for transporting a variable load to a target position. The goal of crane control system is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid tansportation is required. In this paper, we developed a simple fuzzy controller which has been introduced expert's knowledge base for anti-swing and rapid tranportation to goal position. In particular, we proposed the synthesis reasoning method which synthesizes on the basis of expert knowledge of the angle control input and position control input which are inferenced parallel and simultaneously. And we confirmed that the performance of the developed controller is effective as a result of applying it to crane simulator and also verified whether the proposed synthesis rules have been applied correctly using clustering algorithm from the measured data.

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

• Journal of the Korean Society of Industry Convergence
• /
• v.18 no.1
• /
• pp.30-36
• /
• 2015

This paper presents the theoretical development of a complete navigation problem of a nonholonomic mobile robot by using ultrasonic sensors. To solve this problem, a new method to computer a fuzzy perception of the environment is presented, dealing with the uncertainties and imprecision from the sensory system and taking into account nonholonomic constranits of the robot. Fuzzy perception, fuzzy controller are applied, both in the design of each reactive behavior and solving the problem of behavior combination, to implement a fuzzy behavior-based control architecture. The performance of the proposed obstacle avoidance robot controller in order to determine the exact dynamic system modeling system that uncertainty is difficult for nomadic controlled robot direction angle by ultrasonic sensors throughout controlled performance tests. In additionally, this study is an in different ways than the self-driving simulator in the development of ultrasonci sensors and unmanned remote control techniques used by the self-driving robot controlled driving through an unmanned remote controlled unmanned realize the performance of factory antomation.