291 Daehak ro

Yuseong, South Korea

291 Daehak ro

Yuseong, South Korea
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Fraser C.S.R.,77 Massachusetts Ave. | Bertuccelli L.F.,411 Silver Lane | Choi H.-L.,291 Daehak ro | How J.P.,77 Massachusetts Ave.
Automatica | Year: 2012

This paper addresses the problem of information consensus in a team of networked agents by presenting a generic consensus method that permits agreement to a Bayesian fusion of uncertain local parameter estimates. In particular, the method utilizes the concept of conjugacy of probability distributions to achieve a steady-state estimate consistent with a Bayesian combination of each agent's local knowledge, without requiring complex channel filters or being limited to normally distributed uncertainties. It is shown that this algorithm, termed hyperparameter consensus, is adaptable to many local uncertainty distributions within the exponential family, and will converge to a Bayesian fusion of local estimates with some standard assumptions on the network topology. © 2011 Elsevier Ltd. All rights reserved.


Jang Y.J.,291 Daehak ro | Jeong S.,291 Daehak ro | Ko Y.D.,291 Daehak ro
Computers and Industrial Engineering | Year: 2015

We introduce a new type of electric-powered transportation system called the On-Line Electric Vehicle (OLEVTM) developed by Korea Advanced Institute of Science and Technology (KAIST). The battery in the OLEV is charged remotely from power transmitters installed under the road using the innovative wireless charging technology. One of the successful commercial applications of the OLEV is the KAIST shuttle bus system operating on the KAIST campus. In this paper, we address the OLEV's system design issues. The key design and economic parameters of the OLEV are the battery size and the allocation of the power transmitters that wirelessly supply the electric energy to the vehicle. We first construct a general mathematical model for optimally allocating the power transmitters and determining the size of the battery for a transportation system with wireless charging electric vehicles. Then we apply the model to a specific model that is currently operating. We are particularly interested in the OLEV system operating in a closed environment in which vehicles operate under regulated velocity and less traffic. The OLEV shuttle bus currently operating at KAIST is a good example of the system under a closed environment. We are particularly concerned about the closed environment system since it is the potential application area where the OLEV-based transportation is effectively commercialized. The optimization problem is constructed in the form of a Mixed Integer Programming (MIP) model. The sensitivity analysis is presented using the vehicle operational data collected from the OLEV shuttle buses. The sensitivity analysis provides meaningful insight into the OLEV-based transportation system design. We also explain how the general model can be extended to different transportation systems other than the closed environment. © 2014 Elsevier Ltd. All rights reserved.

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