• Journal of Computational Design and Engineering
• /
• 제2권3호
• /
• pp.137-147
• /
• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.907-912
• /
• 1990

An approach to robot force control, which allows force manipulations to be realized without overshot and overdamping while in the presence of unknown environment, is given in this paper. The main idea is to use dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resolved acceleration control method, dynamic compensation and PID control based on known robot dynamics, kinematics and estimated environment compliance is introduced. To avoid overshoot the whole control system is constructed overdamped. In the second stage, the unknown environment stiffness is estimated by using fuzzy reasoning, where the fuzzy estimation rules are obtained priori as the expression of the relationship between environment stiffness and system response. Based on simulation result, comparisons between cases with or without fuzzy identifications are given, which illustrate the improvement achieved.

• 대한토목학회논문집
• /
• 제12권3호
• /
• pp.107-114
• /
• 1992

불투수성 면적의 증가로 인한 유출량의 증가와 홍수도달시간의 단축은 도시홍수에 의한 피해를 가중시키고 있어 이에 대한 대책이 시급한 실정이다. 본 연구에서는 이러한 도시홍수의 방재대책중 하나로 우수배제펌프의 조작기법으로 퍼지제어기법을 적용하여 내수배제능력을 검토하였으며, 기존의 수위기준에 의한 펌프조작기준과 비교하였다. 유수지의 유입량을 산출하기 위해 재현기간 10, 30, 50년의 성계호우를 ILLUDAS 모형에 적용하였다. 퍼지제어규칙의 효용성을 검토하기 위해 퍼지제어규칙 1, 2를 설정하여 가상조작한 결과 조작자의 경험이 포함된 퍼지제어규칙에 의한 펌프제어가 실용적인 면을 보였으며, 내수방재면에서 효과가 있다는 것을 알 수 있었다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.246-251
• /
• 1990

A fuzzy control scheme has been proposed for a supercritical extraction process which has attracted much attention recently as a new separation technology. Based on the manual operation experience, three control pairs between manipulated and output variables are selected first and then seven membership functions are defined for control error and time rate of the error, respectively for each control pair, resulting in forty nine Fuzzy control rules. In addition to these, the membership functions are defined in two steps (coarse and fine) to enhance control performance. Fuzzy inference is performed using MAX-MTN composition rule and defuzzified control output is calculated based on center of gravity method. The prosed Fuzzy control scheme has been assessed through numerical simulation. As a result, the proposed scheme shows good control performance comparable with that by INA(inverse nyquist array) which usually requires complicated design procedure.

• 전자공학회논문지B
• /
• 제30B권4호
• /
• pp.138-147
• /
• 1993

It is known that the performance of a fuzzy controller is related with fuzzification method, inference rules, defuzzification method, and linguistic variables. Among these, generally, the linguistic variables and control rules are transfered to control engineers from an expert or experts of the controlled system and other parts are designed by control engineers. However, there may be some missed infirmations or uncertainties in the transfered data. The purpose of the paper is to propose an algorithm to tune the membership functions of initially given fuzzy sets To do so, a simple shape of the membership fuction is assumed for the fuzzy sets, and the relations between the shapes of the fuzzy sets and the performance of the control system is derived. According to the relations, the shape of the membership functions are modified during operation of the whole system. The proposed algorithm will be applied to two emample plants, type 1 and type 0 systems.

• 대한인간공학회지
• /
• 제19권2호
• /
• pp.87-99
• /
• 2000

This study aims to examine a fuzzy logic-based human expert EMG prediction model (FLHEPM) for predicting electromyographic responses of trunk muscles due to manual lifting based on two task (control) variables. The FLHEPM utilizes two variables as inputs and ten muscle activities as outputs. As the results, the lifting task variables could be represented with the fuzzy membership functions. This provides flexibility to combine different scales of model variables in order to design the EMG prediction system. In model development, it was possible to generate the initial fuzzy rules using the neural network, but not all the rules were appropriate (87% correct ratio). With regard to the model precision, the EMG signals could be predicted with reasonable accuracy that the model shows mean absolute error of 8.43% ranging from 4.97% to 13.16% and mean absolute difference of 6.4% ranging from 2.88% to 11.59%. However, the model prediction accuracy is limited by use of only two task variables which were available for this study (out of five proposed task variables). Ultimately, the neuro-fuzzy approach utilizing all five variables to predict either the EMG activities or the spinal loading due to dynamic lifting tasks should be developed.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.669-675
• /
• 1991

Based on process analysis as well as extensive operation experience, two fuzzy expert control algorithms, for startup and control, are proposed for a supercritical fluid extraction process which has high interacting multivariable structure. In the proposed algorithms, a new simple defuzzification method which only requires four fundamental arithmetic rules is also presented. Through numerical simulations, control performance using the proposed control algorithm is compared with that of a different fuzzy algorithm by an other researcher and that of conventional PID-type controllers which are tuned by well-known optimal criteria. Also, the proposed control algorithm has been tested to the bench scale supercritical fluid extraction process. As a consequence, the proposed fuzzy expert controller has shown fast and robust control performance while the other controllers show sluggish and/or highly oscillatory responses.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.1207-1210
• /
• 1993

There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.1183-1187
• /
• 1993

The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment a noble FLC is proposed, which is based on simple control rules while offering easy tuning of control parameters by utilizing real operation characteristics of an operator. The proposed FLC consists of two parts, the proportional controller part and the FLC part. Experiments are carried out on a test bed which is built around a commercial excavator. The controller is applied to bhe leveling of excavator's bucket tip, which is one of the main functions in an excavator's operation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.811-814
• /
• 1993

The development of fuzzy pan/tilt controller for remote handling in hostile environment is presented in this paper. In remote handling, control of the camera system is somewhat tedious and time consuming. Operators should do the two tasks of manipulating teleoperator and camera pan/tilt at the same time. By automating pan/tilt control, we expect operators could concentrate only on remote operation. When operators control camera pan/tilt they use simple linguistic rules such as "If the position of end effector on TV monitor is at the edge of the screen, control pan/tilt to display the end effector near the center of the screen." Such a rule is similar to fuzzy logic, so we used fuzzy logic controller to control camera pan/tilt. pan/tilt.