• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.10
• /
• pp.1529-1535
• /
• 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.

• Proceedings of the KIPE Conference
• /
• 1998.10a
• /
• pp.125-130
• /
• 1998

This paper presents a speed control for ultrasonic motors using a PI controller and disturbance torque observer. Since the PI gains and the observer's poles are generally fixed, the control performance deteriorates when the driving conditions vary much. Therefore, we propose the speed control scheme that the PI gains and the observer's poles are adjusted on-line in accordance with the speed ripple using fuzzy reasoning.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.10a
• /
• pp.355-358
• /
• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.1
• /
• pp.352-362
• /
• 2014

In this paper, a fuzzy logic controller is designed for a DC motor which can be used for navigation control of mobile robots. These mobile robots can be used for agricultural, defense and assorted social applications. The robots used in these fields can reduce manpower, save human life and can be operated using remote control from a distant place. The developed fuzzy logic controller is used to control navigation speed and steering angle according to the desired reference position. Differential drive is used to control the steering angle and the speed of the robot. Two DC motors are connected with the rear wheels of the robot. They are controlled by a fuzzy logic controller to offer accurate steering angle and the driving speed of the robot. Its location is monitored using GPS (Global Positioning System) on a real time basis. IR sensors in the robot detect obstacles around the robot. The designed fuzzy logic controller has been implemented in a robot, which depicts that the robot could avoid obstacle as well as perform its operation efficiently with remote online control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.2
• /
• pp.115-124
• /
• 2009

This paper proposed an adaptive fuzzy controller for controlling speed and positions of a container crane. The motor used in container crane is installed as SynRM with variable-speed drive having the robustness on the problems of energy and environment. The conventional PI controller is not able to accurately track the position, speed and sway angle of trolley due to the factors of environment and the parameter variety. In the paper, we analyzed the performance of SynRM derive applied to the container crane by using an adaptive fuzzy control of SynRM in order to solve those problems. This paper analyzed the characteristics of position and speed response and compared the performance of PI controller with an adapative Fuzzy controller, proving the validity.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1006-1011
• /
• 2004

Recently, technical trend in machine tools is focused on enhancing of speed, accuracy and reliability. Such high speed usually results in thermal displacement and structural deformation. To minimize such thermal effect, most precision machine tools adopt high precision cooling system. This study proposes a temperature control for an oil cooler system using PI control with fuzzy logic. In a cooler system, the refrigerant flow rate is controlled by rotational speed of the compressor, where the outlet oil temperature is selected as the control variable. The fuzzy control rules iteratively correct PID parameters to minimize the error, difference between the outlet temperature and the reference one. Here, the ambient temperature is used as the reference one. To show the effectiveness of the proposed method, a series of experiments are conducted for an oil cooler system of machine tools, and the results are compared with the ones of a conventional PID control. The experimental results show that the proposed method has advantages of smaller overshoot and smaller steady state error.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.9
• /
• pp.33-43
• /
• 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.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2000.11a
• /
• pp.193-198
• /
• 2000

Switched reluctance motor drives have been finding their applications in the variable speed drives due to their relatively low cost, simple and robust structure, controllability and high efficiency. Fuzzy control does not need any model of plant. It is based on plant operator experience and heuristics. Fuzzy control is basically adaptive and gives robust performance for plant parameter variation. This paper deals with the sped control of switched reluctance motor using fuzzy controller with 7-rule based fuzzy logic. The proposed fuzzy controller is superior to the control performance of the conventional PI controller. The fuzzy controller is implemented by 80C196KC, 16 bit one-chip microcontroller.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• v.3B no.1
• /
• pp.52-58
• /
• 2003

The application of a sliding mode control for improving the dynamic response of an induction motor based speed control system is presented in this paper and provides attractive features, such as fast response, good transient performance, and insensitivity to variations in plant parameters and external disturbance. However, chattering is a difficult problem for which the sliding mode control is a popular solution. This paper presents a new fuzzy-sliding mode controller for a sensorless vector-controlled induction motor servo system to practically eliminate the chattering problem for traction applications. A DSP based implementation of the speed control system is employed. Experimental results are presented using a propulsion system simulator. The performance of the drive is shown to be practically free from chattering.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.28 no.2
• /
• pp.9-18
• /
• 2014

This paper proposes the fuzzy PI controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, this paper proposes the MPPT control using the fuzzy PI controller that can be improve a MPPT control performance. The fuzzy PI controller is adjusted a input of PI controller by fuzzy control and compensated a cumulative error of fuzzy control by PI controller. The fuzzy PI MPPT control is compared to conventional PO and IC MPPT method for various temperature and radiation condition. This paper proves the validity of the fuzzy PI controller using these results.