• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.949-952
• /
• 1993

As well-known, fuzzy control has been recognized to be of great usefulness in many engineering fields. However, the present design methods of fuzzy control systems depend on trial and error the thing that limits its usefulness. Therefore, an effective and convenient support tools for design and evaluation are greatly needed as well as the establishment of the design methods and guidling. From these backgrounds, we have developed a fuzzy control simulator[1, 2] which has various fuzzy control methods such as "direct method", "indirect method" and "fuzzy-PID method". This paper deals especially with the "direct method" function of the simulator. The simulator was developed for personal computers and programed in C language.

• Journal of Mechanical Science and Technology
• /
• v.17 no.2
• /
• pp.221-229
• /
• 2003

In the virtual environment, reality can be enhanced by offering the motion based on a motion simulator in harmony with visual and auditory modalities. In this research the Stewart-Gough-platform-based motion simulator has been developed. Implementation of vehicle dynamics is necessary in the motion simulator for realistic sense of motion, so bicycle dynamics is adopted in this research. In order to compensate for the limited range of the motion simulator compared with the real vehicle motion, washout algorithm composed of high-pass filter, low-pass filter and tilt coordination is usually employed. Generally, the washout algorithm is used with fixed parameters. In this research a new approach is proposed to tune the filter parameters based on fuzzy logic in real-time. The cutoff frequencies of the filters are adjusted according to the workspace margins and driving conditions. It is shown that the washout filter with the fuzzy-based parameters presents better performance than that with the fixed ones.

• Proceedings of the KSME Conference
• /
• 2001.11a
• /
• pp.654-659
• /
• 2001

In the virtual environment, reality can be enhanced by offering the motion based on a motion simulator in harmony with visual and auditory modalities. In this research, the Stewart platform based motion simulator has been developed. This motion simulator is driven by the electric motors, and offers the slightly wider workspace compared to the commercial available simulators. In order to compensate for the limited range of the motion platform, the washout filters with fixed coefficients have been usually adopted. In this paper the new approach is proposed to tune the filter coefficients based on the fuzzy logic on the real-time basis. It is shown that performance with the variable filter coefficients is better than that with the fixed ones. The driving simulator based on the bicycle dynamics was developed by integrating the motion simulator and graphic system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.2
• /
• pp.96-101
• /
• 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 stabley and the study of effectiveness in unmanned operation of cranes.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.24 no.4
• /
• pp.543-554
• /
• 2000

The engineering equations, which have been used in many engineering companies, were employed for the dynamic modelling part in order to develop the naturally circulated boiler simulator. The fuzzy algorithm, which is similar to the algorithm of making decision by the human being, was developed for the boiler simulator controller and its simulated variables were compared with those of classical PID simulations to verify the stability and the effectiveness of fuzzy controller. The simulator is for the naturally circulated boiler and the main components are the furnace, the drum, the super heater, and the economizer. The combustion and thermal radiation dominant equations were used within the furnace and the mass conservation and the energy rate balance equations were employed for the drum part. The heat transfer rates were calculated using the logarithmic mean temperature differences both for the super heater and for the economizer. The simulations are very useful to understand the boiler operations and the engineering design of the main components. The main program was developed under the PC window condition by linking the fuzzy controller to the main boiler program using the Visual C++ language. The various operational conditions such as the abrupt changes of load, the changes of water supply pipes and the diameter of drum were simulated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.268-271
• /
• 1998

this paper presents the potential application of fuzzy logic to the automatic incident detection system. While the conventional incident detection algorithms are based on a binary decision process, the algorithm using fuzzy logic can incorporate ambiguity which occurs in determining incidents. Since collecting good amount of data to construct data base for incidents is pretty expensive, a traffic simulator called FRESIM is used to simulate traffic condition in a freeway. Incident data are obtained by changing input parameters of the simulator and the fuzzy algorithm generates fuzzy rule for determining normal and incident traffic conditions. In this paper, various steps are described to test the algorithm and its results are summarized.

• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.2
• /
• pp.192-199
• /
• 2004

Navigation simulators have been used in many marine schools and manne training centers since the early 1960's. But these simulators were very expens~ve and were almost limited only in one engine system. In this paper, a catamaran with twin engine system. controlled by two remote control levers and its economic simulator based on a personal computer shall be introduced. One of the main features of catamaran is to control variously its progressing direction. In the static state, a catamaran can move into all the directions and in the dynamic state, ship can change immediately the heading and speed. Although a good navigator can skillfully operate one engine system, it is difficult to control smoothly the catamaran of twin engine system without any threat for the safety of passengers. Thus. in order to bring up the expert navigators. the development of a simulator which makes the training effective is necessary, Therefore, in this paper, a Fuzzy Inference Technique based Maneuvering Simulator for catamaran with twin engine system was developed. In general. in order to develop a catamaran simulator for effective training, first of all. its mathematical model must be acquired. According to the acquired system modeling. the dynamics of simulator is determined, But the proposed technique can omit a complex and tedious mathematical modeling procedures by using the fuzzy inference, which dependent upon only experiences of an expert and can design an efficient training program for unskillful navigators. This developed simulator was consisted of two fuzzy inference routines and two remote control levers, and was focused on effective training of navigators for the safe maneuvering to avoid a collision in a harbor.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.3 no.4
• /
• pp.48-59
• /
• 1993

Intellignet control of the dyeing machine is a central part to improve the productivity of autonomous dyeing systems. Recently, many number of control methods are introuduced. One of them is fuzzy logic algorithm. Fuzzy logic based controller has many desirable advantages, which are simple to implement on the real time and need not the information of dynamic characteristics of the systems. In this paper we propose a new dyeing machine control simulator using fuzzy logic algorithm as an approach to develop the intellingent auto-dyeing control system. This developing approach of the fuzzy control simulator is based on linguistic control stratege of experts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.107-111
• /
• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.4
• /
• pp.554-561
• /
• 2013

In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.