• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.117-122
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• 2006

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also this paper is proposed. speed control of induction motor using FLC-FNN and estimation of speed using ANN controller. The back Propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.1-7
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• 2005

This paper is proposed the speed and position sensorless control of surface permanent magnet synchronous motor(SPMSM) with adaptive fuzzy and observer. A adaptive fuzzy controller is applied for speed control of SPMSM drive. A adaptive state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of SPMSM, that employs a d - q rotating reference frame attached to the rotor. A adaptive observer is implemented to compute the speed and position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

• Journal of Power Electronics
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• v.10 no.1
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• pp.65-71
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• 2010

This paper presents the design and implementation of voltage source inverter type SVPWM based speed control of an induction motor using a fuzzy PI controller. This scheme enables us to adjust the speed of the motor by controlling the frequency and amplitude of the stator voltage; the ratio of the stator voltage to the frequency should be kept constant. A model of the fuzzy control system is implemented in real time with a Xilinx FPGA XC3S 400E. It is introduced to maintain a constant speed to when the load varies.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.8-14
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• 2005

This paper is proposed hybrid artificial intelligent(HAI) controller for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on HAI controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. 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 HAI controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.22-28
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• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.780-786
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• 2001

For the compressor speed control of a multi-type air conditioning system, a fuzzy control algorithm was developed. The sum of zone temperature errors and its derivative were used as input variables, and the compressor speed was selected as the output variable. To test the effectiveness of the control algorithm, one outdoor environmental chamber and four indoor environmental chambers were used. In the chambers the zone temperature step change test and the indoor unit change over test were performed. Test results showed that, for the control of compressor speed, the fuzzy control algorithm was more effective than the conventional proportional control algorithm for the energy conservation.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.137-143
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• 1996

The propulsion marine diesel engine has been widely applied with a mechanical-hydraulic governor to control the ship speed for long time. But it was recently very difficult for the mechanical-hydraullic governor to control the speed of engine under the condition of low speed and low load because of jiggling and hunting by rough fluctuation of rotating torque. To solve these problems of control systems, the performance improvement of mechanical-hydraulic governor is required. In this paper, in order to analyze the speed stability of control systems, the influence of parameters of the engine dead time, gain, damping ratio was discussed on the view of control engineering. The performance improvement of a conventional mechanical hydraulic governor is confirmed to be possible by fuzzy control scheme.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.9
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• pp.810-817
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• 2001

Performance of a water-to-water multi-type heat pump system using R22 which has tow indoor units has been investigated experimentally. The refrigerant flow rate of each indoor unit was regulated by an electronic expansion valve and the total refrigerant flow rate of the system was controlled by a variable speed compressor. In the system, evaporator outlet pressure of refrigerant and outlet temperatures of secondary fluid from indoor units were selected as control variables. Experiments were executed for both cooling and heating modes using PID control method with fuzzy logic, and results of the test are compared with a classical PID method. In the case of PID control with fuzzy logic, the fuzzy control rules corrects PID parameters each time. Results show that PID control with fuzzy logic has the merits of quick response and reduced overshoot.

• Journal of the Korean Society of Safety
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• v.14 no.4
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• pp.108-113
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• 1999

This paper presents a study on fuzzy speed and flux controller used in a vector control of a CRPWM(Current Ragulated PWM) induction motor drive. In this paper, an approach for an easier design of the fuzzy controller is presented in order to obtain the desired value for the response time with minimal overshoot and to improve the steady state performance for speed step commands. The fuzzy controller is constructed only upon the knowledge of the motor behaviour and the desired speed response, and provides fast and robust control by reducing the effects of nonlinearities, parameter changes and load disturbance. The results of applying the fuzzy logic controller to an IM drive system are compared with those obtained by application of a conventional PI controller. The fuzzy controller provided a better response than the PI controller.