• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.211-217
• /
• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• 천문학회지
• /
• 제37권5호
• /
• pp.447-454
• /
• 2004

During the hierarchical formation of large scale structure in the universe, the progressive collapse and merging of dark matter should inevitably drive shocks into the gas, with nonthermal particle acceleration as a natural consequence. Two topics in this regard are discussed, emphasizing what important things nonthermal phenomena may tell us about the structure formation (SF) process itself. 1. Inverse Compton gamma-rays from large scale SF shocks and non-gravitational effects, and the implications for probing the warm-hot intergalactic medium. We utilize a semi-analytic approach based on Monte Carlo merger trees that treats both merger and accretion shocks self-consistently. 2. Production of $^6Li$ by cosmic rays from SF shocks in the early Galaxy, and the implications for probing Galaxy formation and uncertain physics on sub-Galactic scales. Our new observations of metal-poor halo stars with the Subaru High Dispersion Spectrograph are highlighted.

• 한국지능시스템학회논문지
• /
• 제11권4호
• /
• pp.311-314
• /
• 2001

최근 지능 정보 처리에 대한 연구가 여러 분야에서 활발히 진행되고 있으며, 불확실하고 복잡한 동적 환경에서도 적응할 수 있도록 그 영역을 확장해 가고 있다. 본 논문에서는 다치 논리함수의 차분의 성질을 이용하여 동적 환경에 적응할 수 있는 다치 오토마타 모델을 제시하였다. 즉, 입력 스트링을 다치 함수의 치에 사상시키고, 다치 함수의 차분의 성질을 상태의 전이에 적용시켜 동적 변화에 자율적으로 적응할 수 있도록 하였다. 따라서, 다치 오토마타는 동적으로 변화하는 환경을 모델링하는데 광범위하게 응용될 수 있을 것이다.

• 한국건축시공학회지
• /
• 제11권1호
• /
• pp.91-99
• /
• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2011년도 제42회 하계학술대회
• /
• pp.1228-1229
• /
• 2011

A novel approach has been promoted for FNN ship controllers. An Electro-hydraulic governor has been widely adopted to the ship speed control of propulsion marine diesel engines for a long time, it was very difficult for Electro-hydraulic governor to regulate the speed of high power engine with long stroke at low speed and low load, because of the jiggling phenomena by rough fluctuation of rotating torque and the hunting phenomena by long dead time occurred in fuel combustion process in the engine cylinder. This paper provides an efficient way for improving control performance by FNN controller. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The performance of controller is evaluated by the system simulation using simulink tools.

• Journal of Communications and Networks
• /
• 제16권2호
• /
• pp.146-154
• /
• 2014

This paper proposes a bandwidth-aware localized-routing algorithm that is capable of sensing the available spectrum bands within a two-hop neighboring for choosing the highly opportunistic routes. A mixed-integer linear programming (MILP) is utilized to formulate the optimization problem. Then, the proposed algorithm is used to determine the maximum bandwidth possible of link pairs via a bandwidth approximation process of relaxed variables. Thereby, the proposed algorithm can allow selected routes corresponding to maximum bandwidth possible between cognitive radio (CR) users through link pairs in cognitive radio networks. By comparing the solution values to previous works, simulation results demonstrate that the proposed algorithm can offer a closed-optimal solution for routing performance in cognitive radio networks. The contribution of this paper is achieved through approximately 50% throughput utilized in the network.

• 전기학회논문지P
• /
• 제59권1호
• /
• pp.29-34
• /
• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• 한국실내디자인학회논문집
• /
• 제14호
• /
• pp.63-73
• /
• 1998

The aim of this study is to understand and redefine the nature of architectural environment within the paradigm of natural science. The chaos theory non-equilibrium thermodynamics theory self-organization of modern physics offer new insights to explain not only natural phenomena but also to define creative and dynamic architectural environment. First natural laws in modern physics like the arrow of time but is related not only with certainty but also possibility so nature is understood as a constantly changing process of evolution. Second the new architectural environment is defined as a kind of fluid and irreducible organic biosytem that cannot be fully understood by modernist idea of architecture. It is conceived of as a fluid constantly changing self-oraganizing system that consists of different situations events movements and programs in uncertain and irreducible time frame. Third insights and implications of natural science offer new language and strategy for design and the two disciplines can be understood as interdependent and co-evolving

• 한국국방경영분석학회지
• /
• 제31권1호
• /
• pp.26-41
• /
• 2005

The ROK TRANSCOM and Army Logistics Command have established wartime overland transportation plans. They have to mobilize several wartime overland transportation troops in order to meet the wartime transportation requirement. But there are some uncertainties in the process of transportation such as the number of vehicles to mobilize, the vehicle utilization factor, and round trip time. Here, we established two models. One is the simulation model to evaluate the transportation capability considering uncertain factors. The simulation model is executed with two scenarios and then the results are analyzed through a sensitivity analysis. The other model is the regression model to analyze the effects of transportation factors toward capability.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1118-1122
• /
• 2005

In order to keep production balance at a mixed-model assembly line and a painting line, large WIP(Work- In-Process) inventories are required between two lines. To increase the efficiency of line handling through reducing the inventories under this circumstance, this paper concerns with a sequencing problem for a mixed-model assembly line that includes a painting line where the uncertain elements regarding the defective products exist. Then, we formulate a new type of the sequencing problem minimizing the line stoppage time and the idle time with forecasting the supply time of the products from the painting line. Finally, we examine the effectiveness of the proposed sequencing through computer simulations.