• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1399-1404
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• 1990

There is an increasing need to apply artificial intelligence to the real application fields of industry. These include an intelligent process control, an expert machine and a diagnostic and/or maintenance machine. These applications are implemented in AI Languages. It is commonly recognized that AI Languages, such as Common Lisp or Prolog, require a workstation. This is mainly due to the fact that both languages need a large amount of memory space and disk storage space. Workstations are appropriate for a laboratory or office environment. However, they are too bulky to use in the real application fields of industry or business. Also users who apply artificial intelligence to these fields wish to have their own operating systems. We propose a new design method of an intelligent controller which is embedded within equipment and provides easy-to-use tools for artificial intelligence applications. In this paper we describe the new design method of a VMEbus based intelligent controller for artificial intelligence applications and a small operating system which supports Common Lisp and Prolog.

• Structural Engineering and Mechanics
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• 제52권5호
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• pp.903-918
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• 2014

Large space structures may have resonant low eigenvalues and often these appear with closely-spaced natural frequencies. Owing to the coupling among modes with closely-spaced natural frequencies, each eigenvector corresponding to closely-spaced eigenvalues is ill-conditioned that may cause structural instability. The subspace to an invariant subspace corresponding to closely-spaced eigenvalues is well-conditioned, so a method is presented to design the feedback control law of intelligent structures with closely-spaced eigenvalues in this paper. The main steps are as follows: firstly, the system with closely-spaced eigenvalues is transformed into that with repeated eigenvalues by the spectral decomposition method; secondly, the computation for the linear combination of eigenvectors corresponding to repeated eigenvalues is obtained; thirdly, the feedback control law is designed on the basis of the system with repeated eigenvalues; fourthly, the system with closely-spaced eigenvalues is regarded as perturbed system on the basis of the system with repeated eigenvalues; finally, the feedback control law is applied to the original system, the first order perturbations of eigenvalues are discussed when the parameter modifications of the system are introduced. Numerical examples are given to demonstrate the application of the present method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.337-342
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• 1998

A new fuzzy control algorithm for the control of active magnetic bearing (AMB) systems is proposed in this paper. It combines PDC design of Joh et al. [8][9] and Namdani-gype control rules using fuzzy singletons to handle the nonlinear characteristics of AMB systems efficiently. They are named fine mode control and rough mode control , respectively. The rough mode control yields the fastest response for large deviation of the rotor and the fine mode control fives desired transient response for small deviation of the rotor. The proposed algorithm is applied a AMB systems to verify the performance of the method, The comparison of the proposed method to a linear controller using a linearized model about the equilibrium point and PDC algorithm in [7] show the superiority of the proposed algorithm.

• 한국지능시스템학회논문지
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• 제6권4호
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• pp.49-60
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• 1996

본 논문의 목적은 신경망을 이용한 퍼지 하이퍼큐브의 적응 학습 제어알고리듬의 개발이다. 퍼지 시스템 규칙베이스 후건부의 실시간적인 수정, 초기 퍼지 제어규칙의 일시적인 안정성을 가정하여 퍼지제어기와 신경망의 장점만을 살린 지능형 제어시스템의 설계방법을 제안하였다. 퍼지 제어기로는 실현 가능한 퍼지 하이퍼큐브의 구조를 선택하였고, 퍼셉트론 신경만의 학습법칙을 적용하여 출력오차로써 퍼지 제어기의 규칙을 실시간적으로 수정해 나가는 방법을 사용하였다. 결과적으로 적응 퍼지-뉴로 제어시스템을 Cart-Pole 제어에 응용함으로써 이러한 지능형 제어기의 유효성과 강인성을 보였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.63-69
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• 2004

In this paper, we propose a general framework for sensor data fusion applied to control systems. Since many kinds of disturbances are introduced to a control system, it is necessary to rely on multisensor data fusion to improve control performance in spite of the disturbances. Multisensor data fusion for a control system is considered a sequence of making decisions for a combination of sensor data to make a proper control input in uncertain conditions of disturbance effects on sensors. The proposed method is applied to a typical control system of a flexible link system in which reduction of oscillation is obtained using a photo sensor at the tip of the link. But the control performance depends heavily on the environmental light conditions. To overcome the light disturbance difficulties, an accelerometer is used in addition to the existing photo sensor. Improvement of control performance is possible by utilizing multisensor data fusion for various output responses to show the feasibility of the proposed method in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.188-196
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• 2016

For the balancing control of a one-wheel mobile robot, CMG (Control Moment Gyro) can be used as a gyroscopic actuator. Balancing control has to be done in the roll angle direction by an induced gyroscopic motion. Since the dedicated CMG cannot produce the rolling motion of the body directly, the yawing motion with the help of the frictional reaction can be used. The dynamic uncertainties including the chattering of the control input, disturbances, and vibration during the flipping control of the high rotating flywheel, however, cause ill effect on the balancing performance and even lead to the instability of the system. Fuzzy compensation is introduced as an auxiliary control method to prevent the robot from the failure due to leaning aside of the flywheel. Simulation studies are conducted to see the feasibility of the proposed control method. In addition, experimental studies are conducted for the verification of the proposed control.

• Journal of Power Electronics
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• 제14권1호
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• pp.74-81
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• 2014

In this study, a brain emotional learning-based intelligent controller (BELBIC) is developed for the speed control of an interior permanent magnet synchronous motor (IPMSM). A novel and simple model of the IPMSM drive structure is established with the intelligent control system, which controls motor speed accurately without the use of any conventional PI controllers and is independent of motor parameters. This study is conducted in both real time and simulation with a new control plant for a laboratory 3 ph, 3.8 Nm IPMSM digital signal processor (DSP)-based drive system. This DSP-based drive system is then compared with conventional BELBIC and an optimized conventional PI controller. Results show that the proposed method performs better than the other controllers and exhibits excellent control characteristics, such as fast response, simple implementation, and robustness with respect to disturbances and manufacturing imperfections.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2008년도 춘계학술대회 논문집
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• pp.391-394
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• 2008

This paper is proposed a high performance speed control of the synchronous reluctance motor through the artificial intelligent SV-PWM. SV-PWM is controlled using fuzzy control that is artificial intelligent control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Fuzzy control has a advantage which can be robustly controlled. Simulation results are presented to show the validity of the proposed algorithm

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.442-442
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• 2000

The intelligent auto-tuning method fur a strongly stable adaptive control system of a DC motor with great load inertia variation is proposed. The stable characteristic polynomial that is designed by an optimal servo is specified for the adaptive pole placement control system. The appropriate adaptive control system can be derived, by adjusting automatically the weight of a performance criterion in optimal control by means of the fuzzy inference on the basis of the stability index.

• 산업융합연구
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• 제22권7호
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• pp.1-13
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• 2024

전자정부 서비스 중 지능형 CCTV 관제 플랫폼은 인공지능을 활용하여 사람, 자동차 등 주요 객체가 CCTV상에 나타났을 경우, 관제요원에게 표출해 주는 선별 관제 서비스이다. 지능형 CCTV 관제 플랫폼을 운영할 경우 비상 상황 발생 시 신속한 대처가 가능하고 민원 해결 증가로 시민들의 삶의 질 제고가 가능할 것으로 기대를 모으고 있다. 이에 본 연구는 비(非)시장재화인 지능형 CCTV 관제 플랫폼의 편익을 선택실험기법인 조건부가치측정법(CVM)을 적용하여 가구당 평균 지불의사액을 추정하고, 이를 토대로 사회적 편익을 계산하였다. 분석 결과 가구의 평균 지불의사액은 연간 6,908원, 국가 전체의 경제적 편익은 연간 약 1,504억 원으로 추정되었다. 본 연구는 그간 환경·공공재의 적용되던 CVM의 적용 범위를 지능형 전자정부 서비스 분야로 확장한 점에서 학술적 의의가 있다. 나아가, 지능형 CCTV 관제 플랫폼 도입이 활발하게 논의되는 현 상황에서, 이에 대한 편익을 화폐가치로 추정하였다는 점에서 실무적 시사점을 지닌다.