• Journal of Mechanical Science and Technology
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• 제18권1호
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• pp.1-11
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• 2004

The ionic Polymer Metal Composite (IPMC) is one of the electroactive polymers (EAP) that was shown to have potential application as an actuator It bends by applying a low voltage current (1∼3 V) to its surfaces when containing water In this paper, the basic characteristics and the static ＆ dynamic modeling of IPMC is discussed. In modeling and analysis, the equations of motion, which describe the total dynamics of the system, are driven. To control the position of the IPMC actuator, an adaptive fuzzy algorithm is used. IPMC is a time varying system because the some parameters vary with the passage of time. In this paper, the modeling and control of IPMC is introduced.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1254-1259
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.373-375
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• 1994

In this paper, the fuzzy LMS algorithm where the convergence coefficient is computed by a fuzzy logic controller was proposed. The proposed fuzzy LMS algorithm showed better convergence property and stability than conventional LMS algorithms. The estimation error and misadaptation degree were used for Input of the fuzzy logic controller. In a airconditioning duct case, various conditions were investigated to design active noise controllers. A case with acoustic feedback, the proposed algorithm showed good performances through computer simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.512-514
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• 1998

The paper presents a model reference adaptive control containing a fuzzy algorithm for tuning the gain coefficient which adjusts the level of the fuzzy controller output. The synthesis of a fuzzy tuning algorithm has been performed for the inverted pendulum system. The computer simulation results have proved the efficiency of the proposed method, showing stable system responses.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.439-443
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• 1996

A fuzzy teaming controller is experimentally designed to control the ball k beam system in this paper. Although most fuzzy controllers have been built just to emulate human decision-making behavior, it is necessary to construct the rule bases by using a learning method with self-improvement when it is difficult or impossible to get them only by expert's experience. The algorithm introduces a reference model to generate a desired output and minimizes a performance index function based on the error and error-rate using the gradient-decent method. In our balancing experiment of the ball ＆ beam system, this paper shows that the fuzzy control rules by learning are superior to the expert's experience.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• Earthquakes and Structures
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• 제21권6호
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• pp.577-585
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• 2021

In this research, a neural network (NN) method was developed, which combines H-infinity and fuzzy control for the purpose of stabilization and stability analysis of nonlinear systems. The H-infinity criterion is derived from the Lyapunov fuzzy method, and it is defined as a fuzzy combination of quadratic Lyapunov functions. Based on the stability criterion, the nonlinear system is guaranteed to be stable, so it is transformed to be a linear matrix inequality (LMI) problem. Since the demo active vibration control system to the tuning of the algorithm sequence developed a controller in a manner, it could effectively improve the control performance, by reducing the wind's excitation configuration in response to increase in the cost efficiency, and the control actuator.

• 한국정보통신학회논문지
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• 제10권9호
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• pp.1718-1726
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• 2006

본 논문에서는 미지의 공간에서 장애물 검출시 스스로 회피를 계획하고 임무를 수행할 수 있는 자율주행 로봇의 주행 알고리즘을 퍼지제어기를 이용하여 설계하였다 장애물의 위치 와 거 리 인식을 위해 초음파센서를 사용하였으며 좌, 우측 바퀴의 각속도 출력 제어를 위하여 퍼지 제어기를 사용하였다. 퍼지제어기의 퍼지화 방법은 싱글톤 방법, 제어규칙은 각 바퀴 49개, 추론법은 간략화 된 Mamdani의 추론법, 비퍼지화 방법은 간략화된 무게중심 법을 사용하였다. 제안한 회피 알고리즘과 퍼지 제어기의 성능 및 실제 적용 가능성의 평가를 위해 이동로봇의 모델링에 근거 한 컴퓨터 시뮬레이션을 수행하였다. 그 결과 이동로봇이 목적지점에 정확히 도착함과 주행 중 인식한 장애물을 효과적으로 회피함을 보였다.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.287-292
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• 2003

로봇의 기능이 다양해지며 복잡해지고 있다. 주위의 환경을 감지하는 센서로는 거리정보 뿐만 아니라 영상 정보, 음성 정보까지 이용하고 있다. 본 논문에서는 다양한 입력정보를 가진 로봇을 제어하기 위한 알고리즘으로 2-layer fuzzy control을 제안한다. 장애물 회피의 경우에 다수의 거리 센서를 이용하는데 이것을 앞쪽, 왼쪽, 오른쪽으로 분류하여 3개의 sub-controller를 가지고 퍼지 추론을 한 다음, 2단계에서는 이 3개의 sub-controller의 출력으로 조합된 퍼지 추론을 하여 통합적인 제어를 한다. 본문에서는 2-layer fuzzy controller와 비슷한 구조를 갖는 hierarchical fuzzy controller와 비교를 하였으며 robot following에도 적용하여 각각에 대한 시뮬레이션과 실험을 통해 성능을 확인한다.

• International Journal of Automotive Technology
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• 제7권2호
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• pp.167-172
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• 2006

A design of controller for vehicle dynamic control(VDC) and its implementation on the real vehicle were introduced. The controller has been designed using a three-degrees-of-freedom(3DOF) yaw plane vehicle, and the control algorithm was implemented on the vehicle by control prototyping system dSPACE. A hybrid control algorithm, which makes full use of the advantages of robust and fuzzy control, was adopted in the control system. Field test results show that the performance of the vehicle handling dynamics with hybrid controller is improved obviously compared to that without VDC and with simple robust controller on skiddy roads(friction coefficients lower than 0.3).