Byung-Hun Lee

Distance-based formation control with a single moving leader

This paper proposes distance-based adaptive formation control laws for the leader-follower system. The developed controller makes all the agents maintain the formation group and move with a constant reference velocity in a plane. It is assumed that there are one leading and two following agents. The leading agent knows the reference velocity whereas the follower does not know the velocity of other agents. Thus, to move in a group, the controller for the follower estimates the reference velocity. An adaptive method is used in the estimation process. The stability and boundedness of the formation are proved by using Lyapunov stability analysis and Barbalats lemma. Simulations results are included to illustrate the validity of the developed theories.

Reliability characteristics of La-doped high-k/metal gate nMOSFETs

The reliability of hafnium oxide gate dielectrics incorporating lanthanum (La) is investigated. nMOSFETs with metal/La-doped high-k dielectric stack show lower V th and I gate , which is attributed to the dipole formation at the high-k/SiO₂ interface. The reliability results well correlate with the dipole model. Due to lower trapping efficiency, the La-doping of the high-k gate stacks can provide better PBTI immunity, as well as lower charge trapping compared to the control HfSiO stacks. While the devices with La show better immunity to positive bias temperature instability (PBTI) under normal operating conditions, the threshold voltage shift (ΔV th ) at high field PBTI is significant. The results of a transconductance shift (ΔG m ) that traps are easily generated during high field stress because the La weakens atomic bonding in the interface layer.

Environmental-Adaptive Bias Calibration in Wireless Localization

This paper presents a simple bias calibration method in wireless localization networks. Based on measured distances between a mobile sensor node and reference beacon sensor nodes fixed at known points, the proposed method estimates the bias error. To compute the bias error accurately, an optimization problem is formulated. Through numerous experiments, the performance of the proposed calibration algorithm is evaluated.

Feasibility Study of

We proposed a Mo/SiOx/Pt resistive random access memory (RRAM) device as an alternative to static random access memory (SRAM) devices for field-programmable gate array (FPGA) applications. In order to evaluate the feasibility of our RRAM device for FPGA applications, we utilized an RRAM device + inverter structure and confirmed its successful operation under various operational schemes, multilevel operation by controlling bias condition, and immunity against read disturbance and a retention test at high temperature. From the nonvolatile and reliable characteristics of our RRAM device, unlike that of SRAM devices, it holds promise to enable reconfigurable logic applications with significantly reduced logic-gate density and power consumption.

\hbox{Mo/SiO}_{x}/\hbox{Pt}

This paper proposes three coordination laws for optimal energy generation and distribution in energy network, which is composed of physical flow layer and cyber communication layer. The physical energy flows through the physical layer; but all the energies are coordinated to generate and flow by distributed coordination algorithms on the basis of communication information. First, distributed energy generation and energy distribution laws are proposed in a decoupled manner without considering the interactive characteristics between the energy generation and energy distribution. Second, a joint coordination law to treat the energy generation and energy distribution in a coupled manner taking account of the interactive characteristics is designed. Third, to handle over- or less-energy generation cases, an energy distribution law for networks with batteries is designed. The coordination laws proposed in this paper are fully distributed in the sense that they are decided optimally only using relative information among neighboring nodes. Through numerical simulations, the validity of the proposed distributed coordination laws is illustrated.

Resistive Random Access Memory in an Inverter Circuit for FPGA Applications

In this paper, we propose a novel distributed orientation estimation method of rigid bodies in n-dimensional space using only relative orientation information. For the orientation estimation, n auxiliary variables for each agent are required. A rotation matrix which identifies orientation of local frame with respect to the common frame is obtained by transforming auxiliary variables with the Gram-Schmidt procedure. Since the auxiliary variables are defined on vector space, a consensus-based control law for auxiliary variables achieves a global convergence. Although there exist initial values of auxiliary variables such that auxiliary variables converge to undesired points, we show that the solution of proposed algorithm can be obtained for almost all initial values.

Distributed Coordination for Optimal Energy Generation and Distribution in Cyber-Physical Energy Networks

Inter-agent formation is the interesting issue and coped within previous literatures. We propose a control strategy based on inter-agent cyclic formulation of nonholonomic model. Graph is directed. Each agent maintains a desired distance with a neighbor agent. Under sliding control technique, sequence of control input forces configuration to equilibrium manifold. Unicycle-like model is used as nonholonomic agent model.

Distributed estimation for the unknown orientation of the local reference frames in N-dimensional space

This paper considers a strategy for energy coordination including flow control and generation in the distributed grid networks. The distributed energy coordination scheme proposed in [5] seeks to achieve the supply-demand balance on the basis of interactions between neighbors. First, details of the algorithm for the distributed energy coordination are described. Then, we provide general solutions for the cases when the supply-demand balance could not be achieved. After providing main analysis for these cases, numerical examples are presented to demonstrate the capability of the proposed analysis.

Nonholonomic control of distance-based cyclic polygon formation

A new hot-carrier injection mechanism that depends on gate bias and body thickness in nanoscale floating-body MOSFETs has been identified using 2-D device simulation and hot-carrier degradation measurements. When gate voltage is sufficiently high and the body thickness is thin, the potential of the floating body is elevated due to the ohmic voltage drop at the source extension (SE), resulting in impact ionization at the SE. Hot-carrier stress with accelerated gate voltage may lead to a huge overestimation of lifetime in nanoscale floating-body MOSFETs.

Energy generation and distribution via distributed coordination: Unbalanced cases

Accurate models for electric power load forecasting are essential to the operation and planning of the electricity in the energy management system(EMS). In the economic dispatch problem, load forecasting helps an electric utility to make important decisions including the battery charging schedule and the generation of electric power. This paper considers several methods for load forecasting based on the neural networks by using selected input candidates. The input variables are analyzed on the characteristic of correlation between weather data and an electrical load. We compare three neural network-based models for predicting the electrical load as follows : Feed Forward Neural Network model(FFNN), Recurrent Neural Network model(RNN) and Neural Network-based nonlinear autoregressive exogenous model(NARX). The subject of load forecasts is the building of the department of mechanical engineering in GIST, Gwangju, Republic of Korea in 2014. Under the proposed models, the predicted load data could be obtained from the selected input data. The simulation results are compared to each model and it shows that the predicted data is accurate and effective.