• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.1
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• pp.29-37
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• 2006

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using learning mechanism-fuzzy neural network(LM-FNN) and ANN(artificial neural network) control. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility md numerical processing capability. Also, this paper proposes speed control of IPMSM using LM-FNN and estimation of speed using artificial neural network 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 back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. Analysis results to verify the effectiveness of the new hybrid intelligent control proposed in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.256-267
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• 2014

An automatic switch among ensembles of clustering algorithms is proposed as a part of the bibliographic big data retrieval system by utilizing a fuzzy inference engine as a decision support tool to select the fastest performing clustering algorithm between fuzzy C-means (FCM) clustering, Newman-Girvan clustering, and the combination of both. It aims to realize the best clustering performance with the reduction of computational complexity from O($n^3$) to O(n). The automatic switch is developed by using fuzzy logic controller written in Java and accepts 3 inputs from each clustering result, i.e., number of clusters, number of vertices, and time taken to complete the clustering process. The experimental results on PC (Intel Core i5-3210M at 2.50 GHz) demonstrates that the combination of both clustering algorithms is selected as the best performing algorithm in 20 out of 27 cases with the highest percentage of 83.99%, completed in 161 seconds. The self-adapted FCM is selected as the best performing algorithm in 4 cases and the Newman-Girvan is selected in 3 cases.The automatic switch is to be incorporated into the bibliographic big data retrieval system that focuses on visualization of fuzzy relationship using hybrid approach combining FCM and Newman-Girvan algorithm, and is planning to be released to the public through the Internet.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.59-62
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture, is systematically conducted for the automatic controlled system. In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA; Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES; Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultiviation results.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2992-2994
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• 2000

In cope with insufficient agricultural labor and requirement of high quality product Hydroponics is a really good method. It makes the high density agriculture possible and all the growing environments controllable. So its research is so much progressing to maximize the quantity and quality of farm products. Furthermore, the big progress, in the research of a future agriculture. is systematically conducted for the automatic controlled system. In this paper, a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA: Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system (FMES: Fuzzy Model-based Expert System) is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller is incorporated to solve the time-variance of the growth of farm products. Finally. the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.313-318
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-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 proposed control algorithm is a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the Adaptive-FNN and ANN controller.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.9
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• pp.43-52
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• 1998

In this paper, a novel type of an integrated controller is designed for vehicles equipped with active classis systems to improve vehicle stability, handling, and ride comfort. The hybrid fuzzy logic controller consists of a fuzzy logic controller, a skyhook controller, an attitude controller, and a roll moment distribution controller, and these controllers are used with a proper combination which is determined by the integrated control logic based on driving conditions of a vehicle. It is shown by simulations using MATRIXx/SYSTEMBBUILD software that ride comfort, handling, and active safety are improved for a 16 degree-of-freedom vehicle dynamic model.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.4
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• pp.51-62
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• 2004

Fuzzy supervisory control technique for the seismic response control of cable-stayed bridges subject to earthquakes is studied. The proposed technique is a hybrid control method, which adopts a hierarchical structure consisting of several sub-controllers and a fuzzy supervisor. Sub-controllers are independently designed to reduced the responses to be controlled of a cable-stayed bridge, and a fuzzy supervisor achieves improved seismic control performance by tuning the pre-designed sub-controllers. It is realized by converting static gains of the sub-controllers into time-varying dynamic gains through the fuzzy inference mechanism. To evaluate the feasibility of the proposed technique, the benchmark control problem of cable-stayed bridge proposed by Dyke et al. is adopted. The control variables for the seismic response control of the cable-stayed bridge are determined to be t도 shear forces and bending moments at the base of the towers, the longitudinal displacements at the top of the towers, the relative displacements between the deck and the tower, and the tensions in the stay cables. Comparative results between the fuzzy supervisory controller and LQG controller demonstrate the effectiveness of the proposed control technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.31-34
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• 1998

본 논문에서는 하이브리드 구조를 가지는 자기구성 퍼지제어기를 제안한다. 제안한 방법은 FARMA 제어기에 비해 다음과 같은 장점을 가진다. 하이브리드 구조를 자기구성 퍼지논리 제어기에 도입하므로써 예측출력값을 구할 때 까지의 입축력정보의 부재로 인한 나쁜 응답성능을 개선할 수 있다. 또한 이 방법은 Yager의 t-norm을 이용하여 계산상의 복잡성을 피하고 규칙들의 가중치를 구하기 위해 필요한 Dmax선정의 어려움을 해결한다.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.1
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• pp.40-45
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• 1996

본 연구는 공정제어를 위한 복합형 퍼지-PID 제어기의 개발에 관한 것이다. 제안된 복합형 퍼지-PID제어기는 퍼지 규칙을 기반으로 한 이득 결정부분({{{{ { K}_{p } { K}_{d } }}}})과 고정이득({{{{ { K}_{i } }}}})을 합친 제어기이다. 모의 실험 결과 제안된 제어기는 고정된 파라메터를 갖는 전통 PID 제어기에 비해 더욱 양호한 제어성능을 나타내었다.