• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.129-139
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• 2010

To be satisfied with complex load condition of electric vehicle, fuzzy logic control (FLC) is applied to improve speed response and system robust performance of induction traction machine based on indirect rotor field orientation control. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels of lightweight electric vehicle by means the vehicle used for passenger transportation. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling, independently, every driving wheel to turn at different speeds in any curve. Our electric vehicle fuzzy inference system control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency and the robustness of the proposed control with good performances compared with the traditional PI speed control, the FLC induction traction machine presents not only good steady characteristic, but with no overshoot too.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.3
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• pp.303-312
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• 2002

In this paper, a fuzzy logic controller(FLC) for parallel operation system of PWM converters with high performances is proposed and a PI controller is also realized to compare with the performances of the proposed FLC. The simulation and experimental results show that performances of the proposed FLC are far more excellent compared with those of PI controller, especially in points of DC voltage transient response characteristics and current control transient response characteristics at step increase of rated load. To verify the superiorities of the proposed FLC and actually apply it in industrial field, Simulation iud experimental results are provided to verify the implemented a PWM converter system with 15kw capacity in paralleled with two 7.5kW PWM converters.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller 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, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning 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.

• Journal of Power Electronics
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• v.3 no.2
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• pp.115-123
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• 2003

This paper presents analysis, design and simulation for the indirect field orientation control (IFOC) of induction machine drive system. The dynamic performance of the IFOC under nominal and detuned parameters of the induction machine is established. A conventional proportional plus integral-derivative (PI-D) two-degree-of-freedom controller (2DOFC) is designed and analysed for an ideal IFOC induction machine drive at nominal parameters with the desired dynamic response. Varying the induction machine parameters causes a degredation in the dynamic response for disturbance rejection and tracking performance with PI-D 2DOF speed controller. Therefore, conventional controllers can nut meet a wide range of speed tracking performance under parameter variations. To achieve high- dynamic performance, a proposed robust fuzzy logic controllers (RFLC) for d-axis rotor flux, d-q axis stator currents and rotor speed have been designed and analysed. These controllers provide robust tracking and disturbance rejection performance when detuning occurres and improve the dynamic behavior. The proposed REL controllers provide a fast and accurate dynamic response in tracking and disturbance rejection characteristics under parameter variations. Computer simulation results demonstrate the effectiveness of the proposed REL controllers and a robust performance is obtained fur IFOC induction machine drive system.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.30-32
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy.

• Journal of Power System Engineering
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• v.20 no.6
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• pp.11-19
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• 2016

A variable speed refrigeration system(VSRS) has been received high attention for energy saving ability. This paper investigates effects of design factors such as membership function range and sampling time to control performances for systematical designing fuzzy logic controller of the VSRS. Some comparisons of control performance between the fuzzy and PI are conducted including comparative evaluation of robustness against noise by using computer simulations. The simulation results showed that the fuzzy is very useful design method for engineers in the industrial fields which have big noises system and deal with inherent nonlinear system like the VSRS.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.488-493
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• 2008

A mathematical model of molten steel level for continuous casting process is presented, where the molten steel level, input and output flow in the mold, the relation between stopper position and input flow etc. are considered. The mathematical model is implemented and simulated by using MATLAB. Comparing the result of molten steel level from the simulator with that of real plant, the performance of the model is shown to be reasonable. By using this simulator, it is shown that PI controller with variable P gain, adjusted by fuzzy logic system, has better control result than conventional PI controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.156-160
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• 1997

In this paper, the control scheme is proposed that PI controller parameter used for TAH speed control is adapted by fuzzy logic method using only the motor current waveform. By scheduling PI parameters, minimization of the vibration and the energy consumption and overcoming AoP loads becomes possible. In in vitro tests experimental results show our approach is a good scheme that is adapted to changing afterloads well.

• Journal of Power Electronics
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• v.9 no.2
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• pp.207-214
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• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.