• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1978-1987
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• 2014

Power requirement to the induction heating system varies during the heating process. A closed loop control is required to have a smooth control over the power. In this work, a constant frequency pulse density modulation based power tracking control scheme for domestic induction heating system is developed using the Fuzzy Logic Controller. In the conventional power modulation schemes, the switching losses increase with the change in the load. The proposed pulse density modulation scheme maintains minimum switching losses for the entire load range. This scheme is implemented for the class-D series resonant inverter system. Fuzzy logic controller based power tracking control scheme is developed for domestic induction heating power supply for various power settings. The open loop and closed loop simulation studies are done using the MATLAB/Simulink simulation tool. The control logic is implemented in hardware using the PIC16F877A microcontroller. Fuzzy controller tracks the set power by changing the pulse density of the gate pulses applied to the inverter. The results obtained are used to know the effectiveness of the fuzzy logic controller to achieve the set power.

• 전기학회논문지
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• 제60권3호
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• pp.471-478
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• 2011

This paper proposes a method of maximum power point tracking (MPPT) using fuzzy logic control for grid-connected photovoltaic systems (PV). First, for the purpose of comparison, because of its proven and good performances, the incremental conductance (IncCond) technique is briefly introduced. A double fuzzy logic controller (DFLC) based MPPT is then proposed which has shown better performances compared to the IncCond MPPT based approach. Modeling and Simulation in grid-connected PV system results are provided for both controllers under same atmospheric condition based PSCAD/EMTDC. The double fuzzy logic MPPT controller is then simulated and evaluated, which has shown better performances.

• 한국정밀공학회지
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• 제16권12호
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• pp.182-189
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• 1999

In this paper, we present an ultrasonic sensor based path planning method using fuzzy logic for obstacle avoidance of an intelligent vehicle in unknown environments. Generally, Robot navigation in unknown terrains is a very complex task difficult to control because of the great amount of imprecise and ambiguous sensor information that has to be considered. In this case, fuzzy logic can satisfactorily deal with such information in quite efficient manner. In this study, we propose two fuzzy logic controller which is composed of steering controller and velocity controller respectively. Our object is to develop a fuzzy controller that can enable a mobile robot to navigate from a start point to a goal point without collisions, in the least possible travel time. The ability and effectiveness for the proposed algorithm will be demonstrated by simulation and expeiment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권3호
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• pp.238-244
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• 2012

A modeling of vision based robot formation control system using fuzzy logic controller and extended Kalman filter is presented in this paper. The main problems affecting formation controls using fuzzy logic controller and vision based robots are: a robot's position in a formation need to be maintained, how to develop the membership function in order to obtain the optimal fuzzy system control that has the ability to do the formation control and the noise coming from camera process changes the position of references view. In order to handle these problems, we propose a fuzzy logic controller system equipped with a dynamic output membership function that controls the speed of the robot wheels to handle the maintenance position in formation. The output membership function changes over time based on changes in input at time t-1 to t. The noises appearing in image processing change the virtual target point positions are handled by Extended Kalman filter. The virtual target positions are established in order to define the formations. The virtual target point positions can be changed at any time in accordance with the desired formation. These algorithms have been validated through simulation. The simulations confirm that the follower robots reach their target point in a short time and are able to maintain their position in the formation although the noises change the target point positions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.509-511
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• 1998

Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership function and fuzzy rule base, which is traditionally achieved by tedious trial-and-error process. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm(GA). The controller design space is coded in base-7 strings chromosomes, where each bit gene matches the 7 discrete fuzzy value. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a do-servo motor control system. It was presented in discrete fuzzy linguistic value, and used a membership function with Gaussian curve. The performance of this control system is demonstrated higher than that of a conventional PID controller and fuzzy logic controller(FLC).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1024-1026
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• 1996

Sources of nonlinearity In a fuzzy logic controller Include the fuzzification, the fuzzy reasoning and the defuzzification. In this paper, a closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two Inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity Is analyzed with respect to the conventional PID control and the sliding mode control.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권2호
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• pp.107-113
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• 2004

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.781-784
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• 1993

Most linguistic models of processes or plants known are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show two models for synchronous finite state machines (FSM) based on fuzzy logic, namely the Crisp-State-Fuzzy-Output (CSFO FSM) and Fuzzy-State-Fuzzy Output (FSFO FSM). As a result of the introduction of the FSM models, the improved architectures for fuzzy logic controller have been defined. These architectures featuring pipelined intelligent fuzzy controller are discussed in terms of dimensionality of the model. VLSI integrated circuit implementation issues of the fuzzy logic controller are also considered. The presented approach can be utilized for fuzzy controller hardware accelerators intended to work in the real-time environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.486-489
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• 1996

The objective of this paper is to design a force feedback controller for bilateral control of a master-slave manipulator system. In a bilateral control system, the motion of the master device is followed by the slave one, while the force applied to the slave is reflected on the master. In this paper, a fuzzy logic controllers applied to the system. Using the fuzzy logic controller, the knowledge of the system dynamics is not needed. Simulations and experimental results show the performance of the proposed controller.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권8호
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• pp.361-366
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• 2001

This thesis proposes a fuzzy logic cross coupled controller for a multi axis servo system. The overall control system consists of three elements: the axial position controller, the speed controller, and a fuzzy logic cross coupled controller. In conventional multi axis servo system, the motion of each axis is controlled independently without regard to the motion of other axes, in which the contour error, defined as the shortest distance between the desired and actual contours is compensated only by the position error of each axis. This decoupled control approach may result in degraded contouring performance due to such factors as mismatch of axial dynamics and axial loop gains. In practice, such systems contain many uncertainties, Therefore, the multi axis servo system must receive and evaluate the motion of all axes for a better contouring accuracy. Cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However the existing cross coupled controllers cannot overcome friction, backlash and parameter variation. Also, since it is difficult to obtain an accurate mathematical model of multi axis system, here we investigate a fuzzy logic cross coupled controller method. Some simulations and experimental results are presented to illustrate the performance of the proposed controller.