• 제어로봇시스템학회논문지
• /
• 제5권7호
• /
• pp.808-813
• /
• 1999

A fuzzy learning method to control an unstable and multivariable system is presented in this paper, Because the multivariable system has generally a coupling effect between the inputs and outputs, it is difficult to find its modeling equation or parameters. If the system is unstable, initial condition rules are needed to make it stable because learning is nearly impossible. Therefore, this learning method uses the initial rules and introduces a cost function composed of the actual error and error-rate of each output without the modeling equation. To minimize the cost function, we experimentally got the Jacobian matrix in the operating point of the system. From the Jacobian matrix, we can find the direction of the convergence in the learning, and the optimal control rules are finally acquired when the fuzzy rules are updated by changing the portion of the errors and error rates.

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 1996년도 추계학술발표회논문집(1)
• /
• pp.73-78
• /
• 1996

In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.

• Journal of applied mathematics & informatics
• /
• 제42권2호
• /
• pp.379-390
• /
• 2024

This study proposes a fuzzy inventory model for managing large-scale production, incorporating cost considerations. The model accounts for two types of expenditure scenarios-parametric and exponential. Uncertainty surrounds holding costs, setup costs, and demand rates. The approach considers a supply chain system with a complex manufacturing process, factoring in transportation costs based on the quantity of goods and distance between the supplier and retailer. The initial crisp model is then transformed into a fuzzy simulation, incorporating specific fuzzy variables affecting inventory costs. The proposed method significantly reduces overall inventory costs for the entire supply chain. Retailer demand is linked to inventory levels, and vendor/distributor storage deteriorates over time. The fuzzy condition assumes hexagonal variables for all associated factors. The study employs the signed distance method for defuzzification to determine the optimal order quantity with hexagonal fuzzy numbers. Mathematical examples are provided to illustrate the practicality of the proposed approach.

• 한국정밀공학회지
• /
• 제12권9호
• /
• pp.95-103
• /
• 1995

Recently the trends toward reduction in size of industrial products have increased the application of micro drilling. But micro drilling has still much difficulty so that the needs for active control which give adaptation to controller are expanding. In this paper initial cutting condition was determined for some sorkpieces by experiment and GA-based Fuzzy controller was devised by genetic algorithms and fuzzy inference. The fuzzy inference has been applied to the various prob- lems. However the determination of the membership function is one of the difficult problem. So we introduce a genetic algorithms and propose a self-tuning method of fuzzy membership function. Based on this intelligent control, automation of micro drilling was carried out like the cutting process of skilled machinist.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 하계학술대회 논문집 B
• /
• pp.390-393
• /
• 1997

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

• 한국항해학회지
• /
• 제8권1호
• /
• pp.15-42
• /
• 1984

Many studies have been done in the field of fuzzy logic theory, but it's application to the ship's steering system is few until this date. This paper is to survey the effect of application of fuzzy logic control by new compositional rule of Inference to the ship's steering system. The controller is made up of a set of Linguistic Control Rules which are conditional linguistic statements connecting the inputs and output, and take the inputs derived from deviation angle and it's angular velocity. The Linguistic Control Rules are implemented on the digital computer to verify the performance of the fuzzy logic controller and simulations have been done in six cases of initial condition and disturbance type. Consequently, it was proved that the ship's steering system by introducing the F.L.C. is performed efficiently and less energy loss system compared with the conventional autopilot.

• 한국컴퓨터정보학회논문지
• /
• 제18권6호
• /
• pp.9-19
• /
• 2013

본 논문에서는 상태 및 출력변수에 시간지연을 가지는 이산 비선형 마코비안 점프시스템의 퍼지 $H_{\infty}$ 필터 설계 방법을 다룬다. 리아프노프(Lyapunov) 함수를 이용하여 상태추정 오차시스템이 확률적 안정하며 외부외란 및 초기값 불확실성에 대하여 $H_{\infty}$ 성능을 만족하는 조건식을 유도하고 필터 존재 조건을 선형행렬부등식으로 나타낸다. 완화된 필터 존재 조건식을 유도하기 위하여 리아프노프 함수 선택 시에 시스템 모드에 종속적일뿐만 아니라 퍼지 멤버십 함수를 포함하는 확률-퍼지 리아프노프 함수를 선택한다. 또한 $H_{\infty}$ 성능 조건식 유도 시에 외부외란 뿐만 아니라 최기값 불확실성을 고려한다. 수치적 예제 및 컴퓨터 시뮬레이션을 통하여 제안된 방법의 타당성을 보인다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제2권1호
• /
• pp.38-42
• /
• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
• /
• pp.86-88
• /
• 1995

This paper presents a design technique of the fuzzy PID controller for power system stabilization. PID parameters of the fuzzy PID controller was self-tuned by the fuzzy inference algorithm. The Nosed controller compare with conventional power system stabilizer(PSS) under various of initial value of rotor angle deviation and load condition. The related simulation results show that the Nosed controller was more excellent control characteristics than conventional PSS in transient-state and steady-state response.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.111-116
• /
• 1998

This paper proposes a robust control using a sliding mode controller and a fuzzy controller. Having the excellent transient response, the sliding mode controller has the poor steady state response, but the fuzzy controller has a good steady state reponse. A proposed controller combined these controllers has the quick response at the initial condition without the errors. The proposed robust nonlinear controller takes the advantage of the fuzzy controller and is the rapid and the stable response in conditions that the sliding mode controller keeps the errors at the steady state. The performance of proposed method is proved by simulation of the inverted pendulum.