• 한국해양공학회:학술대회논문집
• /
• 한국해양공학회 2000년도 추계학술대회 논문집
• /
• pp.79-83
• /
• 2000

A sliding mode fuzzy control (SMFC) with disturbance estimator is applied to design a controller for the third generation benchmark problem on an wind-excited building. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feed-back loop only. General structure of the SMFC is composed of a compensation part and a convergent part. The compensation part prevents the system diverge, and the convergent part makes the system converge to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feed-back loop and a feed-forward loop. To realize the virtual feed-forward loop for the wind-induced vibration control, disturbance estimation filter is introduced. the structure of the filter is constructed based on an auto regressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For the verification of the proposed algorithm, a numerical simulation is carried out on the benchmark problem of a wind-excited building. The results indicate that the present control algorithm is very efficient for reducing the wind-induced vibration and that the performance indices improve as the filter for wind force estimation is employed.

• 시스템엔지니어링학술지
• /
• 제9권2호
• /
• pp.37-53
• /
• 2013

With rapid growth of the world plant market, an increasing attention is paid on the plant engineering. Up to present time, Korean plant engineering technology has been concerned with the down stream part of the plant engineering, so called EPC, considered as a lower value chain compared with the up stream, composed of FEED(Front End Engineering Design) and PMC(Project Management Consultancy). In other words, a key issue for Korean plant industry is how to catch up the FEED technology, currently occupied by the advanced countries. In this paper, we propose an SE(Systems Engineering) approach, conventionally applied for aerospace and defense industry, to the FEED for plant engineering. Specifically, we proposed a new SE process composed of: 1) SPA matrix for reverse systems engineering, and 2) PPA matrix for forward systems engineering. To illustrate the proposed method, a case study for an environmental plant is performed.

• 한국막학회:학술대회논문집
• /
• 한국막학회 2004년도 Proceedings of the second conference of aseanian membrane society
• /
• pp.179-182
• /
• 2004

This study reports the extraction behavior of $\alpha$-lactalbumin using bis(2-ethylhexyl) sulfosuccinate sodium (AOT) reverse micelles. Forward extraction of $\alpha$-lactalbumin in the reverse micellar organic phase from aqueous feed solutions was strongly dependent on the AOT concentration and the complete forward extraction of 0.03 mM $\alpha$-lactalbumin was successfully achieved at an AOT concentration of ca. 100 mM. A similar dependency of the forward extraction on the AOT concentration was obtained in isooctane, n-hexane, and n-octane systems. In the backward extraction from the micellar organic phase, the recovery of the protein as high as ca. 90% was obtained with pH control and/or salt addition.

• Journal of Advanced Marine Engineering and Technology
• /
• 제20권3호
• /
• pp.286-286
• /
• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
• /
• 제20권3호
• /
• pp.154-161
• /
• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 2004년도 춘계 학술발표대회 개요집
• /
• pp.144-145
• /
• 2004

Submerged arc welding technique using metal powder as supplementary filler metal has been studied. Forward feeding was used, and the deposit rate was increased by 50%. Good bead appearance, soundness and mechanical properties were obtained with feed rate of 120g/min..

• 한국통신학회논문지
• /
• 제34권12A호
• /
• pp.933-940
• /
• 2009

본 논문은 시간 선택적 페이딩 (time-selective fading) 채널에 강인한 준직교 시공간 블록 부호(quasi-orthogonal space-time block code) 검출 기법을 제안한다. 제안된 검출 기법은 간섭 제거를 수행하고, 채널이 심벌에서 심벌로 변할 때 안테나 간 간섭 또는 심벌 간 발생하는 간섭을 제거하기 위한 decision-feedback equalization 기능을 수행한다. Feed forward equalizer와 feedback equalizer를 얻기 위해 간섭제거를 수행한 후, 채널 Gram 행렬에 대해 Cholesky 분해를 사용한다. 실험 결과에 의해 제안된 검출 기법의 성능이 time-selectivity 환경에 적용하기 위해 기존에 제안되어온 검출 기법들에 비해 개선되었음을 보인다.

• Journal of Advanced Marine Engineering and Technology
• /
• 제38권1호
• /
• pp.39-47
• /
• 2014

본 연구에서는, 자동으로 조작되는 밸브의 제어기로 사용되는 유압모션 제어기의 한계점인 설정치 추종성능과 외란 억제성능을 개선하기 위한 방법으로 기존의 PID 제어기에 피드-포워드 제어기를 추가한 2자유도(DOF) PID 제어기를 이용하였다. 이 제어기의 제어인자(Parameter)를 최적화시키는 도구로 실수코딩 유전알고리즘(Real Coded Genetic Algorithm, RCGA)을 이용하고 시뮬레이션을 통해 제어기의 성능을 검증하였다.

• 제어로봇시스템학회논문지
• /
• 제21권6호
• /
• pp.518-523
• /
• 2015

This paper proposes a gait phase classifier using a Recurrent Neural Network (RNN). Walking is a type of dynamic system, and as such it seems that the classifier made by using a general feed forward neural network structure is not appropriate. It is known that an RNN is suitable to model a dynamic system. Because the proposed RNN is simple, we use a back propagation algorithm to train the weights of the network. The input data of the RNN is the lower body's joint angles and angular velocities which are acquired by using the lower limb exoskeleton robot, ROBIN-H1. The classifier categorizes a gait cycle as two phases, swing and stance. In the experiment for performance verification, we compared the proposed method and general feed forward neural network based method and showed that the proposed method is superior.

• Smart Structures and Systems
• /
• 제18권6호
• /
• pp.1233-1250
• /
• 2016

Cracks in plate-like structures are some of the main reasons for destruction of the entire structure. In this study, a novel two-stage methodology is proposed for damage detection of flexural plates using an optimized artificial neural network. In the first stage, location of damages in plates is investigated using curvature-moment and curvature-moment derivative concepts. After detecting the damaged areas, the equations for damage severity detection are solved via Bat Algorithm (BA). In the second stage, in order to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, multiple damage location assurance criterion index based on the frequency change vector of structures are evaluated using properly trained cascade feed-forward neural network (CFNN) as a surrogate model. In order to achieve the most generalized neural network as a surrogate model, its structure is optimized using binary version of BA. To validate this proposed solution method, two examples are presented. The results indicate that after determining the damage location based on curvature-moment derivative concept, the proposed solution method for damage severity detection leads to significant reduction of computational time compared with direct finite element method. Furthermore, integrating BA with the efficient approximation mechanism of finite element model, maintains the acceptable accuracy of damage severity detection.