• 한국공작기계학회논문집
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• 제10권2호
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• International Journal of Ocean System Engineering
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• 제1권4호
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• pp.192-197
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• 2011

This paper describes the mathematical modeling, control algorithm, system design, hardware implementation and experimental test of a Manta-type Unmanned Underwater Vehicle (MUUV). The vehicle has one thruster for longitudinal propulsion, one rudder for heading angle control and two elevators for depth control. It is equipped with a pressure sensor for measuring water depth and Doppler Velocity Log for measuring position and angle. The vehicle is controlled by an on-board PC, which runs with the Windows XP operating system. The dynamic model of 6DOF is derived including the hydrodynamic forces and moments acting on the vehicle, while the hydrodynamic coefficients related to the forces and moments are obtained from experiments or estimated numerically. We also utilized the values obtained from PMM (Planar Motion Mechanism) tests found in the previous publications for numerical simulations. Various controllers such as PID, Sliding mode, Fuzzy and $H{\infty}$ are designed for depth and heading angle control in order to compare the performance of each controller based on simulation. In addition, experimental tests are carried out in a towing tank for depth keeping and heading angle tracking.

• 전자공학회논문지SC
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• 제46권3호
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• pp.8-14
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• 2009

본 논문은 성능 향상을 위하여 IMC 제어 구조를 갖는 PID 제어기 설계를 제안했다. 내부 모델은 최종값 정리와 유전자 알고리즘을 이용하여 2차의 지연시간을 갖는 모델로 동정 하였다. 그리고 제어기 파라미터 값은 성능지수 (IAE, ITAE)값이 최소가 되도록 내부 모델과 수치적 계산에 의해서 자동 동조된다. 시뮬레이션을 통하여 다양한 공정에 대하여 본 논문에서 새롭게 제안된 방법이 기존의 방법보다 우수함을 확인 할 수 있었다.

• 대한기계학회논문집A
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• 제28권8호
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• pp.1125-1134
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• 2004

This paper presents a mathematical model which is about the dynamics of not only a two wheel steering vehicle but a four wheel steering vehicle. A sliding mode ABS control strategy and PID rear wheel control logic are developed to improve the brake and cornering performances, and enhance the stability during emergency maneuvers. The performances of the controllers are evaluated under the various driving road conditions and driving situations. The numerical study shows that the proposed full car model is sufficient to accurately predict the vehicle response. The proposed ABS controller reduces the stopping distance and increases the vehicle stability. The results also prove that the ABS controller can be employed to a four wheel steering vehicle and improves its performance. The four wheel steering vehicle with PID rear wheel controller shows increase of stability when a vehicle speed is high and sharp cornering maneuver when a vehicle speed is low compared to that of a two wheel steer vehicle.

• Journal of Astronomy and Space Sciences
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• 제29권4호
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• pp.389-395
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• 2012

The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

• 대한조선학회논문집
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• 제34권3호
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• pp.19-26
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• 1997

본 논문에서는 신경망을 이용한 선박자동조타장치의 개발에 관한 연구결과를 소개한다. 앞의 논문에서 소개된 Back-Propagation 알고리즘을 이용하여 선박의 자동운항을 위한 자동제어방법을 개발하였으며 그 결과 기준모델추구신경망제어기와 순간최적제어기를 설계하였다. 기준모델추구신경망제어기는 선수각과 선수각속도가 주어진 기준모델을 추구하도록 타각을 제어하도록 하였으며, 순간최적제어기는 현 상태에서 다음상태로의 천이를 최적화하도록 하였다. 신경망에 근거한 이들 제어기법을 간단한 선박조종수치모델에 적용한 결과 그 효용성을 확인할 수 있었다.

• 한국공간구조학회논문집
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• 제13권2호
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• pp.37-45
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• 2013

Reduction of microvibration is regarded as important in high-technology facilities with high precision equipments. In this paper, smart control technology is used to improve the microvibration control performance. Mr damper is used to make a smart base isolation system amd fuzzy logic control algorithm is employed to appropriately control the MR damper. In order to develop optimal fuzzy control algorithm, a multi-objective genetic algorithm is used in this study. As an excitation, a train-induced ground acceleration is used for time history analysis and three-story example building structure is employed. Microvibration control performance of passive and smart base isolation systems have been investigated in this study. Numerical simulation results show that the multi-objective genetic algorithm can provide optimal fuzzy logic controllers for smart base isolation system and the smart control system can effectively reduce microvibration of a high-technology facility subjected to train-induced excitation.

• 한국산업정보학회논문지
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• 제13권2호
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• pp.1-7
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• 2008

본 논문은 시스템 인자의 변위에 강인한 연속반복학습제어기(Repetitive Controller RC)를 설계하는 방법을 소개하고자 한다. 이 때 사용되는 불확실 인자들은 확률분포함수에 의해 무작위로 설정되게 된다. 분포함수를 직접 적용하는 대신 본 제어기는 설정된 확률함수로부터 생성된 모형을 기본으로 설계하였다. 이러한 복수모형 설계 기법으로 임의의 분포함수로 구성된 수많은 불확실 인자들을 다룰 수 있다. 그러므로, 제어기는 반복영역에서 수렴성을 보장하는 비용함수를 주파수영역에서 최소화함으로써 유도할 수 있다. 모의실험은 제안된 복수모형설계 기법으로 구한 RC가 단수모형 설계기법을 이용한 RC보다 강인한 것을 보여 주고 있다.

• Smart Structures and Systems
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• 제23권5호
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• pp.467-478
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• 2019

Composite floor structures formed by continuous slab panels may be susceptible to excessive vibrations, even when properly designed in terms of ultimate limit state criteria. This is due to the inherent vibration characteristics of continuous floor slabs composed by precast orthotropic reinforced concrete panels supported by steel beams. These floor structures display close spaced multimode vibration frequencies and this dynamic characteristic results in a non-trivial vibration problem. Structural stiffening and/or insertion of struts between floors are the usual tentative solution applied to existing vibrating floor structures. Such structural alterations are in general expensive and unsuitable. In this paper, this vibration problem is analyzed on the basis of results obtained from experimental measurements in typical composite floors and their theoretical counterpart obtained with computational modeling simulations. A passive control system composed by multiple synchronized dynamic attenuators (MSDA) was designed and installed in these floor structures and its efficiency was evaluated both experimentally and through numerical simulations. The results obtained from experimental tests of the continuous slab panels under human walking dynamic action proved the effectiveness of this control system in reducing vibrations amplitudes.

• 한국지진공학회논문집
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• 제10권6호
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• pp.93-102
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• 2006

대형 구조물에 작용하는 큰 외력은 능동 제어 장치의 제어입력에 포화를 종종 유발한다. 그리고 구조물이 대형화될수록 질량, 강성 등의 파라미터들에 대한 정확한 값을 알기가 어려워지므로, 수학적인 모델과 실제 구조물과의 모델링 오차는 파라미터들에 대한 불확실성으로 제어기의 설계 시에 고려되어야 한다. 그러므로 건축 및 토목 구조물에 대한 능동 진동 제어 방법을 다룰 때 제어기의 안정성을 보장하기 위하여 제어입력의 포화와 계의 파라미터 불확실성을 동시에 고려한 강인 포화 제어기의 설계가 필요하다. 여기에서는 건물의 능동 진동 제어에 연구 및 적용되어진 여러 제어기들 중에서 선형 최적 제어기 LQR, 수정된 뱅뱅 제어기, 포화 슬라이딩 모드 제어기, 강인 포화 제어기의 안정성을 살펴본다. 특히 제안된 강인 포화 제어기의 필요성을 보이기 위하여 LQR, 수정된 뱅뱅 제어기, 포화 슬라이딩 모드 제어기들이 제어입력의 포화나 파라미터 불확실성이 존재하는 경우에 불안정해지는 현상들을 보인다. 2자유도 진동계에 대한 수치 예제와 능동 질량 감쇠기(AMD)를 이용한 2층 구조물에 대한 실험을 통하여 강인 포화 제어기의 강인 안정성을 보인다.