• Journal of the Korean Data and Information Science Society
• /
• 제25권6호
• /
• pp.1491-1498
• /
• 2014

최적실험의 제일 큰 약점은 실험기준이 지나치게 모형과 그에 수반되는 가정에 의존한다는 점이다. 이는 종종 모형의 모수의 개수와 받힘점의 개수가 일치를 하는 경우로 이루어지는데 이는 가정된 모형이 참이 아닌 경우를 대비한 실험이 될 수 없다. 이런 경우 문헌에서는 가정된 다항회귀모형의 차수보다 큰 차수를 가진 다항회귀모형을 가정하고 최적실험을 제안하나 이는 D-효율에 근거한 관행적인 방법일 뿐이다. 본 연구에서는 O'Brien (1995)이 제안한 가정된 모형의 일반적인 이탈을 염두에 둔 추가받힘점 생성에 관하여 알아보고 단순회귀모형과 2차 회귀모형에 대한 실험들을 D-효율로 카타로그화 하여 실험자로 하여금 선택을 할 수 있게 하였다. O'Brien은 비선형모형에 대해 추가받힘점의 선택 방법을 제시하였지만 방법을 구현하는 데 있어 명확치 않은 기준이 있어 모수에 의존하는 비선형모형에 대한 최적실험보다는 다항회귀모형을 중심으로 심층적으로 사용방법을 알아보았다.

• KIEE International Transactions on Power Engineering
• /
• 제5A권3호
• /
• pp.269-279
• /
• 2005

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to find the optimal switch position because of its numerous local minima. In this investigation, a parallel AEA was developed for the reconfiguration of the distribution system. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of GA and the local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC-cluster system consisting of 8 PCs·was developed. Each PC employs the 2 GHz Pentium IV CPU, and is connected with others through switch based fast Ethernet. The new developed algorithm has been tested and is compared to distribution systems in the reference paper to verify the usefulness of the proposed method. From the simulation results, it is found that the proposed algorithm is efficient and robust for distribution system reconfiguration in terms of the solution quality, speedup, efficiency, and computation time.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2000년도 추계학술대회논문집
• /
• pp.282-286
• /
• 2000

In this paper, magneto-rheological(MR) damper is studied for vibration control of large infra structures under earthquake. Generally, active control devices need a large control force and a high power supply system to reduce the vibration effectively. Large and miss tuned control force may induce the dangerous situation such that the generated large control force acts to amplify the structural vibration. Recently, to overcome the weaknesses of the active control, the semi-active control method is suggested by many researchers. Semi-active control uses the passive control device of which the characteristics can be modified. Control force of the semi-active device is not generated from the actuator with power supply. It is generated as a dynamic reaction force of the device same as in the passive control case, so the control system is inherently stable and robust. Unlike the case of passive control, control force of semi-active control is adjusted depending on the measured response of the structure, so the vibration can be reduced more effectively against various unknown environmental loads. Magneto-rheological(MR) damper is one of the semi-active devices. Dynamic characteristics of the MR material can be changed by applying the magnetic fields. So the control of MR damper needs only small power. Response time of MR to the input voltage is very short, so the high performance control is possible. MR damper has a high force capacity so it is adequate to the vibration control of large infra structure. Because MR damper has a nonlinear property, normal control method used in active control may not be effective. Clipped optimal control, modified bang-bang control etc. have been suggested to MR damper by many researchers. In this study, sliding mode fuzzy control(SMFC) is applied to MR damper. Genetic algorithm is used for the controller tuning. To verify the applicability of MR damper and suggested algorithm, numerical simulation on the aseismic control is carried out. Simulation model is three-story building structure, which was used in the paper of Dyke, et al. The control performance is compared with clipped optimal control. The present results indicate that the SMFC algorithm can reduce the earthquake-induced vibration very effectively.

• 미래기술융합논문지
• /
• 제2권2호
• /
• pp.9-14
• /
• 2023

이 연구는 1050MPa급 경량 연성 주철 주관류 컨트롤 암을 개발하기 위한 첫 해의 결과를 보여줍니다. 첫째, 최적 설계 구조를 위한 레이아웃 설계 및 구성 요소 개발, 그리고 컨트롤 암 강성과 최적 구조 디자인 및 강건성 설계를 통해 예상 응력을 제어하는 중점 영역의 강건성을 달성합니다. 둘째, 높은 강성과 고성능 경량 구조를 반영하는 컨트롤 암을 개발합니다. 중공을 통해 소비자가 요구하는 설계와 강성을 충족시키기 위해 개발된 컨트롤 암은 코어 제작 공정을 개발합니다. 셋째, 최적의 합금 조성과 열처리 방법을 통해 철 합금 (Cu, Ni, Mo)의 양과 Austempered 열처리 및 조화 상태를 도출합니다. 넷째, 저강도, 고강성 구성 요소 개발을 위해 최적의 성형기술 개발을 통해 최적의 주조 기술 개발로 이어지는 구성 요소 개발을 위한 높은 강도의 주조 형성 기술을 개발하기 위한 시도를 합니다.

• 한국전산구조공학회논문집
• /
• 제36권6호
• /
• pp.399-405
• /
• 2023

본 연구에서는 철근콘크리트 모멘트골조의 보-힌지 붕괴 기구를 유도하기 위한 유전자알고리즘 기반의 최적내진설계기법을 제시한다. 제안하는 기법은 두 가지의 목적함수을 사용한다. 첫 번째는 구조물의 비용을 최소화하는 것이고, 두 번째는 구조물의 에너지소산능력을 최대화하는 것이다. 제약조건은 기둥과 보의 강도조건, 기둥-보 휨강도비 최소 조건, 기둥의 소성힌지 발생 방지조건 등이 사용된다. 부재의 강도 평가를 위해 선형정적해석이 수행되고, 에너지소산능력과 소성힌지 발생여부를 평가하기 위해 비선형정적해석이 수행된다. 제안하는 기법은 4층 예제 구조물에 적용되었으며, 보-힌지 붕괴 기구를 유도하는 설계안이 얻어지는 것을 확인하였다. 획득된 설계안의 기둥-보 휨강도비를 분석한 결과, 그 값은 기존 내진 기준에서 제시하는 값보다 큰 것으로 나타났다. 보-힌지 붕괴 모드를 유도하기 위해서는 보다 더 강화된 전략이 필요하다.

• Transactions on Control, Automation and Systems Engineering
• /
• 제4권1호
• /
• pp.62-74
• /
• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.438-443
• /
• 2003

In this paper, we propose a control algorithm for two-wheel mobile robot that can move the rider to his or her command and autonomously keep its balance. The control algorithm is based on a mixed $H_2/H_{\infty}$ control scheme. In this control problem the main issue is to move the rider while keeping its balance in the presence of disturbances and parameter uncertainties. The disturbance force caused by uneven road surfaces and the uncertainty due to different rider's heights are considered. To this end we first consider a state feedback controller as a basic framework. Secondly, we obtain the state feedback gain $K_2$ minimizing the $H_2$ norm and the state feedback gain $K_{\infty}$ minimizing the $H_{\infty}$ norm over the whole range of parameter uncertainty. Finally, we select mixed $H_2$/$H_{\infty}$ state feedback controller K as the geometric mean of $K_2$ and $K_{\infty}$. Simulation results show that the mixed $H_2/H_{\infty}$ state feedback controller combines the effects of the optimal $H_2$ state feedback controller and robust $H_{\infty}$ controller state feedback controller efficiently in the presence of disturbance and parameter uncertainty.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.316-321
• /
• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, 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 direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• International Journal of Control, Automation, and Systems
• /
• 제5권6호
• /
• pp.674-680
• /
• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Journal of Electrical Engineering and Technology
• /
• 제12권2호
• /
• pp.944-949
• /
• 2017

Recently, the demand of maglev systems in the manufacturing industry for LCD and OLED display panels, which are required to be very clean and possess vacuum systems, has been increasing due to their characteristics such as being non-contact, noise free and eco-friendly. However, it is still a challenge to simultaneously control both the propulsion and levitation for their interactive effect difficult to be exactly measured. In this paper, we proposed a new tuning method for controlling the magnetic levitation force robustly against the levitation disturbance caused by a propulsion system, based on LQ servo optimal control. The disturbance torque of the LSM propulsion system is calculated through FEM analysis in such a way that the LQ servo controller is determined in order to minimize the effect of the disturbance. The robust performance of the proposed LQ servo control method for the in-track type magnetic levitation systems is demonstrated via simulations and experiments.