• Ocean Systems Engineering
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• 제10권4호
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• pp.373-397
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• 2020

Heave compensation is a vital part of various marine and offshore operations. It is used in various applications, including the transfer of cargo between two vessels in the open ocean, installation of topsides of an offshore structure, offshore drilling and for surveillance, reconnaissance and monitoring. These applications typically involve a load suspended from a hydraulically powered winch that is connected to a vessel that is undergoing dynamic motion in the ocean environment. The goal in these applications is to design a winch controller to keep the load at a regulated height by rejecting the net heave motion of the winch arising from ship motions at sea. In this study, we analyze and compare the performance of various control algorithms in stabilizing a suspended load while the vessel is subjected to changing sea conditions. The KCS container ship is chosen as the vessel undergoing dynamic motion in the ocean. The negative of the net heave motion at the winch is provided as a reference signal to track. Various control strategies like Proportional-Derivative (PD) Control, Model Predictive Control (MPC), Linear Quadratic Integral Control (LQI), and Sliding Mode Control (SMC) are implemented and tuned for effective heave compensation. The performance of the controllers is compared with respect to heave compensation, disturbance rejection and noise attenuation.

• Nuclear Engineering and Technology
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• 제55권12호
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• pp.4647-4658
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• 2023

In this paper, elastic-plastic fracture mechanics analysis is performed to determine the critical crack sizes of the multipurpose canister (MPC) manufactured using austenitic stainless steel under dynamic loading conditions that simulate drop accidents. Firstly, dynamic finite element (FE) analysis is performed using Abaqus v.2018 with the KORAD (Korea Radioactive Waste Agency)-21 model under two drop accident conditions. Through the FE analysis, critical locations and through-thickness stress distributions in the MPC are identified, where the maximum plastic strain occurs during impact loadings. Then, the evaluation using the failure assessment diagram (FAD) is performed by postulating an external surface crack at the critical location to determine the critical crack depth. It is found that, for the drop cases considered in this paper, the principal failure mechanism for the circumferential surface crack is found to be the plastic collapse due to dominant high bending axial stress in the thickness. For axial cracks, the plastic collapse is also the dominant failure mechanism due to high membrane hoop stress, followed by the ductile tearing analysis. When incorporating the strain rate effect on yield strength and fracture toughness, the critical crack depth increases from 10 to 20%.

• 전자공학회논문지S
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• 제36S권7호
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• pp.104-115
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• 1999

본 논문은 세 개의 카메라로부터 얻어진 영상에서 표면 깊이 정보를 재구성하여 얼굴의 3차원 모델을 생성하는 효율적인 방법을 제안한다. 논문에서는 Trinocular 영상을 사용하여 binocular 영상 사용 시 발생하는 폐색 영역 문제와 깊이 해상도 한계를 개선하였다. 또한, MPC_MBS (Matching Pixel Count Multiple Baseline Stereo) 유사도 측정 방법을 제안하여 영상 정합 시 발생하는 Boundary overreach 현상을 줄이고 정합의 정확도와 정밀도를 개선하였다. 이 방법은 정합 때 발생하는 중복 계산을 제거함으로써 계산 시간도 줄일 수 있다. 모델 생성 시에는 추출된 변위 정보를 2차원 보간에 의해 소수점 단위까지 확장하여 연속적인 표면 깊이 정보를 추출하였고, 이로부터 일정 간격의 초기 삼각형 매쉬 모델을 생성하였다. 또한 삼각형 매쉬 모델의 데이터 크기를 줄이기 위하여 사용자가 지정하는 오차 이내에서 같은 평면으로 근사화 되는 꼭지점을 병합하는 알고리듬을 제안하여 효율적인 얼굴 모델 생성이 이루어지도록 하였다.

• 한국융합학회논문지
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• 제4권3호
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• pp.43-50
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• 2013

This paper presents a model predictive control (MPC) based on a neural network (NN) model for air/fuel ration (AFR) control of automotive engines. The novelty of the paper is that the severe nonlinearity of the engine dynamics are modelled by a NN to a high precision, and adaptation of the NN model can cope with system uncertainty and time varying effects. A single dimensional optimization algorithm is used in the paper to speed up the optimization so that it can be implemented to the engine fast dynamics. Simulations on a widely used mean value engine model (MVEM) demonstrate effectiveness of the developed method.

• 로봇학회논문지
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• 제19권1호
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• pp.8-15
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• 2024

This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H_∞ optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1435-1437
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• 2003

In this paper, we proposed static output feedback model predictive control for Wiener models. We adopted polytopic uncertainty description of Wiener Model Predictive Control (WMPC) algorithms for considering output nonlinearities. Robust stability conditions have been presented under which the closed loop stability of static output feedback MPC is guaranteed. The proposed control law is determined from the static output feedback WMPC based on the current estimated state with explicit satisfaction of input constraints.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2014년도 추계학술대회 논문집
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• pp.21-22
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• 2014

본 논문은 5-레벨 NPC/H-브릿지 (Neutral Point Clamped/H-bridge) 인버터의 최적 제어 세트 (finite-control-set) 모델 예측 제어 (MPC: Model Predictive Control) 방법을 제안한다. NPC/H-브릿지 인버터의 출력 전류 제어 및 DC-link 커패시터 전압 균형을 유지하기 위해 출력 전류와 DC-link 커패시터 전압을 예측하고, 하나의 비용 함수 (cost function)을 통해 최적의 스위칭 상태를 출력한다. PSIM 시뮬레이션을 통해 제안된 제어 알고리즘의 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.27.4-27
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• 2001

A stabilizing control method for linear systems with model uncertainties and hard input constraints is developed, which does not require on-line optimizations. This work is motivated by the constrained robust MPC(CRMPC) approach [3] which adopts the dual mode prediction strategy (i.e. free control moves and invariant set) and minimizes a worst case performance criterion. Based on the observation that, a feasible control sequence for a particular state can be found as a linear combination of feasible sequences for other states, we suggest a stabilizing control algorithm providing sub-optimal and feasible control sequences using pre-computed optimal sequences for some canonical states. The on-line computation of the proposed method reduces to simple matrix multiplication.

• 천문학회보
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• 제46권1호
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• pp.36.1-36.1
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• 2021

Galaxy clusters host Mpc-scale diffuse radio emission giving us evidence of large-scale magnetic fields in the Universe. It is relevant to understand magnetic field amplification processes occurring at the center and outskirts of galaxy clusters. Each of these processes are believed to give rise to observed radio haloes and radio relics, respectively. In this work, we focus on studying the continuum and polarised emission in radio relics. We use threedimensional magnetohydrodynamical simulations of merger shock waves propagating through a magnetized, turbulent intracluster medium. Our model includes the diffusive shock acceleration (DSA) of cosmic ray electrons, their spatial advection and energy losses at run-time. We discuss the relation between the mock observation features and the underlying morphology of the magnetic field.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.