• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.299-308
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• 1998

In this paper, reliable switched reluctance motor(SRM) drive system and 4-rule based fuzzy logic modifier(FLM) of the conventional PI controller are presented. The i80C196KC, low-cost one-chip microcontroller is used for designing SRM drive controller which include the speed controller and the starting sequence. The fuzzy logic modifier which exhibits a stabilizing effects on the closed-loop system, has good robustness regarding the improperly tuned PI controller. The simulation and experimental results are performed to verify the capability of proposed control method on 6/4 salient type SRM.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.209-216
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• 1996

This paper deals with the speed control of the switched reluctnace motor using fuzzy PI controller. A fuzzy logic control provides a good approach to nonlinear system because it does not require a detailed mathematical model to formulate the algorithm. The fuzzy PI controller is implemented by MCS80C196KB, a 16 bit one-chip microcontroller, and an EPROM is used for the commutation logic of the SRM. The simulation and experimental results show that the performance of the fuzzy PI controller is superior to that of the conventional PI controller in terms of response time, settling time and overshoot. In particular, the robustness of the system is largely improved.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.200-203
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• 1998

In this paper, it deals with Switched Reluctance Motor(SRM) which has fuzzy logic contoroller(FLC). The modeling and FLC of SRM are presented. The modeling and FLC of SRM are presented. The results of simulation show the speed responce characteristics of SRM with FLC. As a result, the SRM controller with FLC is verified by comparison between PI controller and fuzzy logic controller.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.234-239
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• 2009

In this article we present the simulation results of induction motor speed regulation by direct torque control with a classic PI regulator. The MATLAB Simulink programming environment is used as a simulation tool. The results obtained, using a fuzzy logic, shows the importance of this method in the improvement of the performance of such regulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.891-894
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• 1993

To improve limitations of fuzzy PI controller especially when applied to high order systems, we propose two types of fuzzy logic controllers that take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional fuzzy PI controllers. The structures of the proposed controller were motivated by the problems of fuzzy PI controllers that they generally give inevitable overshoot when one tries to reduce rise time of response especially when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. Since the undesirable characteristics of the fuzzy PI controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response, we propose two fuzzy controllers that fuzzily clear out integrated quantities according to situation. The first contr ller determines the fuzzy resetting rate by situations described fuzzily by error and error rate, and the second one by error and control input. The two structures both give reduced rise time as well as small overshoot. To show the usefulness of the proposed controller, that are applied to systems that are difficult to get satisfactory response by conventional fuzzy PI controllers.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1246-1253
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• 2009

This paper presents derived a calculating form of fuzzy inference, based on decomposition of $\alpha$-level sets. Based on the calculating form it is propose that fuzzy logic circuits of PI+PD controller are a body from fuzzy inference to defuzzificaion in cases where the command variable u directly is generated PWM. The effect of quantization on $\alpha$-levels is investigated. with input/out characteristics of fuzzy controller by simulation. It is concluded that 4 quantization levels are sufficient result for fuzzy control performance of DC servo system. Simulation and experimental results demonstrated that the hardware implementation of the proposed controller can successfully provide good performance on the position control of DC servo system.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1147-1150
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• 2001

This paper represents a realization of a fuzzy PI control method for a speed control of BLDC motor. In other words, the gains of the PI controller is tuned by a fuzzy logic controller. Simplified reasoning methods are used for fuzzy reasoning. Fuzzy logic speed controller is designed by using the high performance of DSPchip(TMS320F240). By experiment, it is confirmed that the speed of BLDC motor well follows an command speed in the load variables or speed variables.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.838-840
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• 1997

This presents a design method for fuzzy logic controllers of TCSC using genetic algorithm. Fuzzy logic controllers are applied to damp the dynamic disturbances sum as sudden changes of AC system loads. The dynamic performances of fuzzy logic controllers are compared with those of PI controllers. The simulation results show that dynamic performances of fuzzy controllers have better response than those of PI controllers when the AC system load changes.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.164-170
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• 2013

Quadrotor UAV (Unmanned Aerial Vehicle) is a flying robotic platform which has drawn lots of attention in the recent years. The attraction comes from the fact that it is able to perform agile VTOL (Vertical Take-Off Landing) and hovering functions. In addition, the efficient modular structure composed of four electric rotors makes its design easier compared to other single-rotor type helicopters. In many cases, a quadrotor often utilizes vision systems in order to obtain altitude control and navigation solution in hostile environments where GPS receivers are not working or deniable. For carrying out their successful missions, it is essential for flight control systems to have fast and stable control responses of heading angle outputs. This paper presents a Fuzzy Logic based lateral PI controller to stabilize and control the quadrotor vehicle equipped with vision systems. The advantage of using the fuzzy based PI controller lies in the fact that it could acquire a desired output response of a heading angle even in presence of disturbances and uncertainties. The performance comparison of the newly proposed Fuzzy-PI controller and the conventional PI controller was carried out with various simulation results.