• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1168-1172
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• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 B
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• pp.1235-1237
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• 1992

In this paper, a new PWM method and estimating means of rotor position angles for BLDC motor drive are presented. The rotor position angles is predicted by calculated rotor flux from the stator voltage and current signals. The current control PWM using fuzzy logic is also suggested. Performance of the proposed controller is observed through a simulation.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2008년도 춘계학술대회 논문집
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• pp.440-444
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• 2008

The 7-phase BLDC motor is possible for higher efficiency per the unit area, high power and high speed due to the increasing number of phase. Also, it can be looking forward to reduce the current ripple at a point of commutation by the increasing number of phase. Thus, a study for applications of servo system, medical and military instruments is progressing about the BLDC motor is manufactured with multi-phase, currently. This paper is used the fuzzy logic control method for speed control of 7-phase BLDC motor and this is compared with the conventional PI controller using by simulation and experimental results for verification validity of the fuzzy logic controller in this system. The 7-phase BLDC motor and controller are modeled by PSIM6.0 software of PowerSim co. in simulation and we are experimented by the test board that is composed with TMS320VC33-150 DSP controller of Texas Instruments co. and FLEX EPF6016TC144-3 of ALTERA co.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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• pp.520-527
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• 2008

This work focuses on the evaluation of active power filter which is controlled by fuzzy logic and neural network based controller for harmonic mitigation and power factor enhancement. The APF consists of a variable DC voltage source and a DC/AC inverter. The task of an APF is to make the line current waveform as close as possible to a sinusoid in phase with the line voltage by injecting the compensation current. The compensation current is estimated using adaptive neural network. Using the estimated current, the proposed APF is controlled using neural network and fuzzy logic. Computer simulations of the proposed APF are performed using MATLAB. The results show that the proposed techniques for the evaluation of APF can reduce the total harmonic distortion less than 3% and improve the power factor of the system to almost unity.

• Smart Structures and Systems
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• 제13권3호
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• pp.473-500
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• 2014

Tuned mass dampers (TMDs) have been installed in many high-rise buildings, to improve their resiliency under dynamic loads. However, high-rise buildings may experience natural frequency changes under ambient temperature fluctuations, extreme wind loads and relative humidity variations. This makes the design of a TMD challenging and may lead to a detuned scenario, which can reduce significantly the performance. To alleviate this problem, the current paper presents a proposed approach for the design of a robust and efficient TMD. The approach accounts for the uncertain natural frequency, the optimization objective and the input excitation. The study shows that robust design parameters can be different from the optimal parameters. Nevertheless, predetermined optimal parameters are useful to attain design robustness. A case study of a high-rise building is executed. The TMD designed with the proposed approach showed its robustness and effectiveness in reducing the responses of high-rise buildings under multidirectional wind. The case study represents an engineered design that is instructive. The results show that shear buildings may be controlled with less effort than cantilever buildings. Structural control performance in high-rise buildings may depend on the shape of the building, hence the flow patterns, as well as the wind direction angle. To further increase the performance of the robust TMD in one lateral direction, active control using LQG and fuzzy logic controllers was carried out. The performance of the controllers is remarkable in enhancing the response reduction. In addition, the fuzzy logic controller may be more robust than the LQG controller.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권10호
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• pp.587-594
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• 2002

A low frequency square wave electronic ballast for the high intensity discharge(HID) lamps using fuzzy logic controller is developed. This electronic ballast consists a buck converter, a low frequency square wave full bridge inverter, a high voltage pulse generator for the HID lamp ignition, an over current protection circuit and an 8-bit microcontroller. The ballast system is operated on the constant current mode during the HID lamp start-up process and the system is operated on the constant power mode during steady state. Experimental results show that the fuzzy logic control operation is carried out successfully by the 8-bit microcontroller PIC16F877 In this electronic ballast system, in spite of the limited control bandwidth caused by low operating speed of the microcontroller, the good performance in the constant lamp current characteristic is obtained. Acoustic resonance of the HID lamps can be effectively avoided because the instantaneous In lamp power is fully constant due to the low frequency square wave drive.

• 조명전기설비학회논문지
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• 제25권9호
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• pp.33-43
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• 2011

Since the fuzzy neural network(FNN) is universal approximators, the development of FNN control systems have also grown rapidly to deal with non-linearities and uncertainties. However, the major drawback of the existing FNNs is that their processor is limited to static problems due to their feedforward network structure. This paper proposes the recurrent FNN(RFNN) for high performance and robust control of SynRM. RFNN is applied to speed controller for SynRM drive and model reference adaptive fuzzy controller(MFC) that combine adaptive fuzzy learning controller(AFLC) and fuzzy logic control(FLC), is applied to current controller. Also, this paper proposes speed estimation algorithm using artificial neural network(ANN). The proposed method is analyzed and compared to conventional PI and FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• 전기학회논문지
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• 제61권10호
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• pp.1529-1535
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• 2012

This paper presents the application algorithm for speed control of Switched Reluctance Motor. The conventional PI controller has been widely used in industrial applications. But it is very difficult to find the optimal PI control gain. Fuzzy control does not need any model of plant. It is based on plant operator experience and heuristics. The proposed fuzzy logic modifier increases the control performance of conventional PI controller. Simulation and experimental results show that the proposed fuzzy control method was superior to the conventional PI controller in the respect of system performance. The experiments are performed to verify the capability of proposed control method on 6/4 salient type SRM.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1474-1477
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• 2005

This paper is proposed maximum torque per ampere of induction motor using fuzzy-neural networks controller. Operation of maximum torque per ampere is achieved when, at a given torque and speed, the slip frequency is adjusted to that so that the stator current amplitude is minimized. This paper introduces a induction motor drive system with fuzzy-neural networks controller. A neural network-based architecture is described for fuzzy logic control. The characteristic rule and their membership function of fuzzy system are represented as the processing nodes in the neural network structure. This paper is proposed the analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of Power Electronics
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• 제12권5호
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• pp.800-812
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• 2012

This paper analyses the mathematical model and control strategies of a Hybrid Active Power Filter with Injection Circuit (IHAPF). The control strategy based on the load harmonic current detection is selected. A novel control method for a IHAPF, which is based on the analyzed control mathematical model, is proposed. It consists of two closed-control loops. The upper closed-control loop consists of a single fuzzy logic controller and the IHAPF model, while the lower closed-control loop is composed of an Adaptive Network based Fuzzy Inference System (ANFIS) controller, a Neural Generalized Predictive (NGP) regulator and the IHAPF model. The purpose of the lower closed-control loop is to improve the performance of the upper closed-control loop. When compared to other control methods, the simulation and experimental results show that the proposed control method has the advantages of a shorter response time, good online control and very effective harmonics reduction.