• Journal of Industrial Technology
• /
• v.13
• /
• pp.43-48
• /
• 1993

In this paper, a new PID fuzzy controller (FC) is presented. The linguistic control rules of PID FC is separated into two parts : one is $e-{\Delta}e$ part, and the other is ${\Delta}^2e-{\Delta}e$ part. And then two FCs employing these rule base indivisually are synthesized. The control input to the process is decided by taking weighted mean of the outputs of two FCs. The proposed PID FC improve the transient response of the system and gives better performance than the conventional PI FC.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.221-224
• /
• 2000

We consider one of robust controller, fuzzy-sliding mode controller dealing with model uncertainty, simplified representation of nonlinear system, changed parameters of plant. We propose fuzzy-sliding mode algorithm which provides control input that has system states approaching the choosed sliding surface. This fuzzy controller has a rule base to get initial states converged on sliding surface. This algorithm Is applied to a transfer function of DC motor to be modeled simply and do position control of DC motor due to system parameters. We compare fuzzy-sliding mode controller to both sliding mode controller and fuzzy controller to identify roust control.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.12
• /
• pp.1870-1883
• /
• 1993

In this paper, in order to build up the User Network Interface based on ATM, a study on traffic control techniques which should be performed by main function groups-B 75,5 NT2, LEX-is discussed. The structure of B-NT2 which is the most important function group In the User Network Interface is defined in quite a simple manner in addition, the functional blocks of LEX are defined in a similar manner as those of B NT2. It is possible to distribute total traffic control functions by using the similarities between B-NT2 and LEX and by allocating virtual path identifiers fixedly according to the characteristics of the traffics. For the traffic control techniques of ATM, relations among Connection Admtsslon Control, Usage Parameter Control and Bandwidth Allocation Control are defined and Multi Rule Base structure to realize optimal control functions according to the characteristics of the source traffics is proposed. And the Real-time Variable Window algorithmsimply designed to be suitable for the Multi Rule Base architecture is also proposed. The performances of the proposed algorithm are analyzed through the computer simulation by generating on-off source traffic in a virtual system that has the form of the proposed hardware. The analyzed results show that the distributed control is possible and that the implementation of the proposed architecture and algorithm is possible.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1228-1229
• /
• 2011

A novel approach has been promoted for FNN ship controllers. An Electro-hydraulic governor has been widely adopted to the ship speed control of propulsion marine diesel engines for a long time, it was very difficult for Electro-hydraulic governor to regulate the speed of high power engine with long stroke at low speed and low load, because of the jiggling phenomena by rough fluctuation of rotating torque and the hunting phenomena by long dead time occurred in fuel combustion process in the engine cylinder. This paper provides an efficient way for improving control performance by FNN controller. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The performance of controller is evaluated by the system simulation using simulink tools.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1703_1704
• /
• 2009

Fuzzy neural ship controllers is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using simulink tools.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.253-257
• /
• 2000

the objective of this study is to design and evaluate a methodology for diagnosing the appendicitis in a fuzzy neural network that integrates the partition of input space by fuzzy entropy and the generation of fuzzy control rules and learning algorithm. In particular the diagnosis of appendicitis depends on the rule of thumb of the experts such that it associates with the region, the characteristics, the degree of the ache and the potential symptoms. In this scheme the basic idea is to realize the fuzzy rle base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by back propagation learning rule. To eliminate the number of the parameters of the rules, the output of the consequences of the control rules is expressed by the network's connection weights. As a result we obtain a method for reducing the system's complexities. Through computer simulations the effectiveness of the proposed strategy is verified for the diagnosis of appendicitis.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.671-672
• /
• 2008

Hybrid intelligent technique is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using Matlab.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.3
• /
• pp.119-124
• /
• 2014

In this paper, we propose the active rule system applying with emotional margin for power saving control. The proposed system in this paper is a part of the system which derives smart power saving by adjusting the illuminance using active rules within compromising the user's emotion. For this, we set the specific range of standard illuminance and the lower bound of user's emotional margin of illuminance based on measurements and analysis, and use these data in design of active rules. And then, we design and implement the active rule system using mobile agent. The mobile agent in the proposed system migrates to the destination sensor nodes, acquires and transmits sensor data according to the purpose and needs through the active rules, and directly executes the actions corresponding to the optional events(changed sensor data and/or time etc.). And then, we show the potential applicability of the proposed active rule system in various active sensor network applications through the interaction with the rule base and mobile sensor network middleware system.

• Fashion & Textile Research Journal
• /
• v.11 no.4
• /
• pp.648-660
• /
• 2009

In this research, an expert system has been developed to select optimum well-matched fusible interlinings with a face fabric. First, a database of face fabrics and fusible interlinings has been constructed. And knowledge acquisition has been performed from the previous studies about the properties of fusible interlinings and fused composites as well as fusing prsocess quality control. Then, a rule-based knowledge-base has been constructed through knowledge classification. Finally, we have constructed an inference engine with the knowledge-base. The expert system enables us to easily select optimum fusible interlinings for a face fabric considering high quality fused composites and fashion trend.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.3
• /
• pp.30-37
• /
• 2004

This thesis develops a fuzzy-PID control algorithm for control the filament winding tension. It is developed by applying classical PID control technique to a fuzzy logic controller. It is composed of a fuzzy-PI controller and a fuzzy-D controller. The fuzzy-PI controller uses error and integrated error as inputs, and the fuzzy-D controller uses derivative of error as input. The fuzzy-PI controller uses Takagi-Sugeno fuzzy inference system, and the fuzzy-D controller uses Mamdani fuzzy inference system. The fuzzy rule base for the fuzzy-PI controller is designed using 19 rules, and the fuzzy rule base for the fuzzy-D controller is designed using 5 rules. A test-bed is set-up for verifying the effectiveness of the developing control algorithm in control the filament winding tension. It is composed of a mandrel, a carriage, a force sensor, a driving roller, nip rollers, a creel, and a real-time control system. Nip rollers apply a vertical force to a filament, and the driving roller drives it. The real-time control system is developed by using MATLAB/xPC Target. First, experiments for showing the inherent problems of an open-loop control scheme in a filament winding are performed. Then, experiments for showing the robustness of the developing fuzzy-PID control algorithm are performed under various working conditions occurring in a filament winding such as mandrel rotating speed change, carriage traversing, spool radius change, and reference input change.