• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.3-8
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• 2000

This paper describes a development of self tuning scheme for PI and PO type fuzzy controllers. The output scaling factor(SF) is adjusted on-line by fuzzy rules according to the current trend of the controlled process. The rule-base for tuning the output SF is defined on error and change of error for the controlled variable using the most natural and unbiased membership functions. Simulation results demonstrate the better control performance can be achieved in comparison with Ziegler-Nichols(Z-N) PID controllers.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2839-2842
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• 1999

This paper describes the design of fuzzy PID controller using simplified indirect inference method. First, the fuzzy PID controller is derived from the conventional continuous time linear PID controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional PID controller, which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• 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.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1400-1407
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• 2015

In the paper, we suggest bettered EHMECS(Enhanced Hybrid Multi Electrical Cupping System) to regulate automatically vacuum pressure using many cupping cup at once. We controlled accurately the pressure using S-PI control technique in pump motor to input the air inside cupping cup. S-PI control compared constant velocity, load and velocity variance between existing PI and FLC(Fuzzy Logic Control). The stabilization time of suggested S-PI control improve 20% of existing PI and 8% of FLC. The error constant of normal condition improved 71% of existing PI and 62% of FLC in steady speed and 80% of existing PI and 67% of FLC in load change. Also the error constant about velocity variance improve 45% of PI control. It is prove the suggested S-PI control technique. When use long time vacuum pressure of cupping cup regulated the suggested S-PI control technique, can loosen knotted muscles.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.63-64
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• 2015

제어 대상이 다양해지고, 제어 변수도 다양해짐에 따라 기존의 PID 제어 시스템으로는 설계자가 원하는 응답 특성을 이끌어내기 어려워지고 있다. 제어 대상의 복잡도가 증가함에 따라 제어 대상에 대한 사용자의 숙련도 또한 제어 품질의 중요 변수이다. 사람의 경험을 제어에 체계적으로 반영하려는 시도 중에 하나가 퍼지이론의 제어 적용이며, 본 논문에서는 간단한 퍼지 제어 시스템을 구현하여 모터 제어에 활용가능성을 확인하고자 한다. 매트랩을 이용한 모의 실험을 통해, 쿼드콥터의 모터에 대하여 PID 제어와 Fuzzy 제어를 적용시켜 그 성능을 비교 및 분석하였다.

• Journal of Power Electronics
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• v.11 no.6
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• pp.914-921
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• 2011

Commencing with incandescent light bulbs, every load today creates harmonics. Unfortunately, these loads vary with respect to their amount of harmonic content and their response to problems caused by harmonics. The prevalent difficulties with harmonics are voltage and current waveform distortions. In addition, Electronic equipment like computers, battery chargers, electronic ballasts, variable frequency drives, and switching mode power supplies generate perilous amounts of harmonics. Issues related to harmonics are of a greater concern to engineers and building designers because they do more than just distort voltage waveforms, they can overheat the building wiring, cause nuisance tripping, overheat transformer units, and cause random end-user equipment failures. Thus power quality is becoming more and more serious with each passing day. As a result, active power filters (APFs) have gained a lot of attention due to their excellent harmonic compensation. However, the performance of the active filters seems to have contradictions with different control techniques. The main objective of this paper is to analyze shunt active filters with fuzzy and pi controllers. To carry out this analysis, active and reactive current methods ($i_d-i_q$) are considered. Extensive simulations were carried out. The simulations were performed under balance, unbalanced and non sinusoidal conditions. The results validate the dynamic behavior of fuzzy logic controllers over PI controllers.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.14-21
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• 2007

Sight Stabilization system is the control system to preserve Line of Sight for the targets though many nonlinear disturbances and vibrations are generated. In this paper, we identified Stabilization system using RLS algorithm, one of the system identification algorithm and found out the modeling of system. Considering nonlinear operational condition this paper proposes two Knowledge-base controllers - Fuzzy controller, Fuzzy PI Gain Scheduling controller, and simulates the performances of proposed controllers compare with Lead PI controller being used in Sight system of NFIV.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.4
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• pp.1-7
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• 2009

The surge control system in unmanned turbojet engine must be capable of accounting uncertainties from engine transient conditions, random fluctuations of key parameters such as air pressure and fuel flow and engine modeling errors. In this paper, taking into consideration of its effectiveness as well as system stability, a fuzzy PI controller is proposed. The role of the fuzzy PI controller is to stabilize the unmanned aircraft upon occurring unexpected engine surge. The proposed control scheme is proved by computer simulation using a linear engine model. The simulation results on the state space model of a small turbojet engine illustrate the proposed control system achieves the desired performance.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1114-1115
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• 2007

In this paper, a new speed sensorless control based on a fuzzy compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional proportional plus integrate(PI) control are very sensitive to step change of the command speed, parameter variations and load disturbance. To cope with these problems of the PI control, the estimated speeds are compensated by using the fuzzy logic controller (FLC). In the FLC used by the speed compensator of the IPMSM, the system control parameters are adjusted by the fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.