• 제어로봇시스템학회논문지
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• 제12권3호
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• pp.227-232
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• 2006

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear system which may also contain system uncertainties. The continuous-time uncertain TS fuzzy model is first contructed to represent the uncertain nonlinear system. A parallel distributed compensation(PDC) technique is then used to design a fuzzy-model-based controller for both stabilization. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using a globally intelligent digital redesign method. This new technique is designed by a global matching of state variables between analog control system and digital control system. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear systems with uncertainties. Finally, Chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 F
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• pp.2653-2655
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• 1999

A technique to suppress the low frequency ripple voltage of the DC output voltage in three-phase buck diode rectifiers is presented. A pulse frequency modulation method is employed to regulate the output voltage of the rectifier and guarantee zero-current switching of the switch over the wide operating range. The pulse frequency control method used in this paper shows generally good performance such as low THD of the input line current and unity power factor. In addition, the pulse frequency method can be effectively used to suppress the low frequency voltage ripple appeared in the dc output voltage. The proposed technique illustrates its validity and effectiveness through the respective simulations and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2187-2189
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• 2003

This paper presents a design method of the wavelet neural network(WNN) controller based on a direct adaptive control scheme for the intelligent control of chaotic systems. The conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on a direct adaptive control method is proposed to control chaotic systems whose mathematical models are not available. The gradient-descent method is used for training a wavelet neural network controller. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic system.

• 대한의용생체공학회:의공학회지
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• 제15권4호
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.54-59
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• 2006

The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.70-78
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• 2004

This paper proposes non-linear control method using immune algorithm based fuzzy logic. Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because gain of the PID controller has to be manually tuned by trial and error. An inverted pendulum control problem is selected to illustrate the efficiency of the proposed method and defines relationship state variables $\chi$, $\chi$, $\theta$, $\theta$ using immune fuzzy.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.606-613
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• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.624-627
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• 1996

To provide pleasant building environment and the ease of maintenance and facility management, many new office buildings are being built as intelligent buildings. Building control systems which are employed in intelligent buildings require advanced types of controllers and varieties of control schemes. Designing and installation of these types of advanced building control systems take a lot of effort and also they are costly. In order to design these systems, it is necessary for the designers to have means to analyze and estimate the performance of control systems. The simulator which is presented in this paper is composed of three parts, HVAC simulation module, elevator simulation module, and evacuation modeling module for the outbreak of fire or similar disasters. In this paper, the functions and modelling method for each module are explained and simulation results are presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권4호
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• pp.293-298
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• 2006

In this paper, a sensor fusion based robot navigation method for the autonomous control of a miniature human interaction robot is presented. The method of navigation blends the optimality of the Fuzzy Neural Network(FNN) based control algorithm with the capabilities in expressing knowledge and learning of the networked Intelligent Robotic Space(IRS). States of robot and IR space, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.

• 한국지능시스템학회논문지
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• 제12권5호
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• pp.417-423
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• 2002

본 논문에서는 자연언어를 이용하는 인간의 학습방법에 기초한 LIBL방법을 선박의 조타 시스템에 적용하여, 항해사의 조타명령과 같은 언어적 지시가 조타수를 경유하여 수행되는 과정을 대체하는 지능형 조타 제어 시스템을 제안하고자 한다. 구체적인 연구방법으로는 조타수의 적절한 조타조작모델을 퍼지추론 규칙을 이용하여 구현하고, 적절한 의미소 및 평가규칙을 제시한 언어지시 기반 학습방법을 선박의 조타시스템에 적용하여, 항해사의 언어지시에 보다 효율적으로 응답하는 지능형 조타기 제어 시스템을 구현한다. 퍼지추론을 이용하여 조타수의 경험을 바탕으로 한 타 조작 모델을 구축하였고, 지능형 조타 시스템을 위한 타각, 방위도달시간, 정상상태의 의미소를 제안하여, 조타수 조작 모델 규칙을 수정하기 위한 평가 규칙을 제시하였다. 또한, 구축된 선박조종 시뮬레이터에 제안된 시스템을 적용하여 그 유효성을 확인하였다.