• 제어로봇시스템학회논문지
• /
• 제5권4호
• /
• pp.427-436
• /
• 1999

This paper describes an ECG signal labeling algorithm based on fuzzy clustering, which is very useful to the automated ECG diagnosis. The existing labeling methods compares the crosscorrelations of each wave form using IF-THEN binary logic, which tends to recognize the same wave forms such as different things when the wave forms have a little morphological variation. To prevent this error, we have proposed as ECG signal labeling algorithm using fuzzy clustering. The center and the membership function of a cluster is calculated by a cluster validity function. The dominant cluster type is determined by RR interval, and the representative beat of each cluster is determined by MF (Membership Function). The problem of IF-THEN binary logic is solved by FCM (Fuzzy C-Means). The MF and the result of FCM can be effectively used in the automated fuzzy inference -ECG diagnosis.

• 제어로봇시스템학회논문지
• /
• 제12권6호
• /
• pp.561-567
• /
• 2006

This paper deals with a fuzzy controller using IA(Immune Algorithm) for Trajectory Tracking of 2-DOF WMR(Wheeled Mobile Robot). The global inputs to the WMR are reference position and reference velocity, which are time variables. The global output of WMR is a current position. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities on the track of trajectory is necessary. Therefore, a FIAC(Fuzzy-IA controller) is proposed to give velocity compensation in this system. Input variables of fuzzy part are position errors in every sampling time. The output values of fuzzy part are compensation velocities. IA are implemented to adjust the scaling factor of fuzzy part. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 하계학술대회 논문집 D
• /
• pp.2283-2285
• /
• 2001

This paper proposed to a neural network based fuzzy control (neuro-fuzzy control) technique for attitude control of helicopter with strongly dynamic nonlinearities and derived a helicopter aerodynamic torque equation of helicopter and the force balance equation. A neuro-fuzzy system is a feedforward network that employs a back-propagation algorithm for learning purpose. A neuro-fuzzy system is used to identify nonlinear dynamic systems. Hence, this paper presents methods for the design of a neural network(NN) based fuzzy controller(that is, neuro-fuzzy control) for a helicopter of nonlinear MIMO systems. The proposed neuro-fuzzy control determined to a input-output membership function in fuzzy control and neural networks constructed to improve through learning of input-output membership functions determined in fuzzy control.

• 조명전기설비학회논문지
• /
• 제27권11호
• /
• pp.20-26
• /
• 2013

This paper proposes the maximum power point tracking(MPPT) control of photovoltaic system using fuzzy based variable step size perturbation & observation(FVSS-PO) method. Conventional PO and incremental conductance(IC)MPPT control algorithm generally uses fixed step size. A small fixed step size will cause the tracking speed to decrease and tracking accuracy of the MPP will decrease due to large fixed step size. Therefore, the fixed step size can't be satisfying both the tracking speed and the tracking accuracy. This paper proposes FVSS-PO MPPT algorithm that adjusts automatically step size of PO by fuzzy control according to operating conditions. The validity of MPPT algorithm proposed in this paper prove through compare with conventional PO MPPT algorithm.

• 한국정보통신학회논문지
• /
• 제5권5호
• /
• pp.977-984
• /
• 2001

본 논문에서는 유전자-퍼지 제어 알고리즘에 대하여 논의하고 그 성능을 평가하였다. 이 알고리즘은 퍼지 논리와 유전자알고리즘의 융합된 형태이며, 제어 대상으로는 도립진자 시스템을 모델링 하였다. 퍼지 제어기는 두 개의 입력과 한 개의 출력 변수를 설계하기 위해 적용되며, GA(Genetic Algorithm)는 퍼지 규칙과 소속 함수를 선택, 교차, 돌연변이의 진화 연산을 통해 최적화한다. 컴퓨터 시뮬레이션에 퍼지 제어의 경우 초기 함수 f(0.3, 0.3)일 때 최대 언더슈트가 $-5.0 \times 10^{-2}[rad]$, 최대 오버슈트가 $3.92\times10^{-2}[rad]$으로 측정되었으나, 유전자 퍼지 알고리즘의 경우 최대 오버슈트와 언더슈트가 각각 0.0[rad]으로 측정되었다. 또한 정상상태 도달시간이 퍼지제어의 경우 2.12[sec], 유전자-퍼지 알고리즘은 1.32[sec]로 비교적 안정적으로 나타났다. 컴퓨터 시뮬레이션으로 이 알고리즘을 도립진자 시스템에 적용시키고, 그 성능의 우수성과 효율성을 증명하였다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2008년도 하계종합학술대회
• /
• pp.1073-1074
• /
• 2008

This paper presents outdoor reset control based on fuzzy algorithm for radiant floor heating system. We construct fuzzy system under indoor temperature and outdoor temperature. Simulation is based on TRNSYS with MATLAB. MATLAB is calculating and decide heat source using fuzzy system. Energy efficiency of Fuzzy algorithm is analyzed in term of indoor by TRNSYS System.

• 한국지진공학회:학술대회논문집
• /
• 한국지진공학회 2005년도 학술발표회 논문집
• /
• pp.469-476
• /
• 2005

To date, many viable smart base isolation systems have been proposed. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively. A fuzzy logic controller (FLC) is used to modulate the MR damper. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find appropriate fuzzy rules and the GA-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

• 대한전기학회논문지:전력기술부문A
• /
• 제49권3호
• /
• pp.95-106
• /
• 2000

The load frequency control of power system is one of important subjects in view of system operation and control. That is even though the rapid load disturbances were applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow one on each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation were given, the unstable phenomenal of power system can be often brought out because of the large frequency deviation and the unsuppressible power line one. Therefore, it is desirable to design the robust neuro-fuzzy controller which can stabilize effectively the given power system as soon as possible. In this paper the robust neuro-fuzzy controller was proposed and applied to control of load frequency over multi-area power system. The architecture and algorithm of a designed NFC(Neuro-Fuzzy Controller) were consist of fuzzy controller and neural network for auto tuning of fuzzy controller. The adaptively learned antecedent and consequent parameters of membership functions in fuzzy controller were acquired from the steepest gradient method for error-back propagation algorithm. The performances of the resultant NFC, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the load frequency control of multi-area power system, when the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbances of internal parameters and external stepwise load stepwise load changes, the superiorities of the proposed NFC in robustness and adaptive rapidity to the conventional controllers were proved.

• 제어로봇시스템학회논문지
• /
• 제5권8호
• /
• pp.990-994
• /
• 1999

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm uses fuzzy algorithm for its speed control and neuralnetwork for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제5권2호
• /
• pp.124-130
• /
• 2005

Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.