• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.2
• /
• pp.121-126
• /
• 2000

In the fast sampling limit the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that covers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control system The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• ETRI Journal
• /
• v.32 no.5
• /
• pp.795-800
• /
• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.6
• /
• pp.1886-1902
• /
• 2000

RBAC(Role Based Access Control) is an access control method based on the user's roles and it provides more flexibility and applicability on the various computer and network security fields than DAC(Discretionary Access Control) or MAC(Mandator Access Control). In this paper, e newly propose ERBAC\ulcorner(Extended RBAC\ulcorner) model by considering subject's and object's roles and security levels for roles additionally to RBAC\ulcorner model which is firstly proposed by Ravi S. Sandhu as a base model. The proposed ERBAC\ulcorner model provides finer grained access control with multilevel security on he base of subject and object level than RBAC\ulcorner model.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.6
• /
• pp.2427-2433
• /
• 2015

This paper presents an observer-based robust controller for constant reference tracking of linear time invariant systems with polytopic model uncertainties. To this end, this paper not only designs a robust integral controller gain but also suggests how to determine the robust observer gain and the observer model used in the observer. Since the observer model selection is not obvious due to the polytopic uncertainties, particular attention needs to be paid to that. This paper computes the robust controller and observer gains first. Then, the observer model is selected in a way that the whole closedloop is stable and LMIs are used in the middle of choosing the gains and observer model. Simulation examples show that the proposed observer-based feedback control successfully achieves robust reference tracking.

• Structural Engineering and Mechanics
• /
• v.26 no.4
• /
• pp.377-392
• /
• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.40 no.2
• /
• pp.148-158
• /
• 1998

The aims of this study are to evaluate the application on the stress-strain behavior of granite Soil using Lade's double work hardening constitutive model based on the theories of elasticity and plasticity. From two different sites of construction work, two disturbed and compacted weathered granite samples which are different in partical size and degree of weathering respectively were obtained. The specimen employed were sampled at Iksan and Pochon in order to predict the constitutive model. Using the computer program based on the regression analysis, 11 soil parameters for the model were determined from the simple tests such as an isotropic compression-expansion test and a series of drained conventional triaxial tests. In conclusion, it is shown that Lade's double work hardening model gives the good applicability for processing of stress-strain, work-hardening, work-softening and soil dilatancy. Therefore, this model in its present form is applicable to the compacted decomposed granite soil.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.11a
• /
• pp.161-164
• /
• 2006

The sales of consumer durables are composed of first time purchases and replacement purchases. Since the sales for most mature durable products are dominated by replacement sales, it is necessary to develop a model incorporating replacement component of sales in order to forecast total sales accurately. Several single product diffusion models incorporating replacement demand have been developed, but research addressing the multi-product diffusion models has not considered replacement sales. In this paper, we propose a model based on consumer choice behavior that simultaneously captures the diffusion and the replacement process for multi-product relationships. The proposed model enables the division of replacement sales into repurchase by previous users and transition purchase by users of different products. As a result, the model allows the partitioning of the total sales according to the customer groups (first-time buyers, repurchase buyers, and transition buyers), which allows companies to develop their production and marketing plans based on their customer mix. We apply the proposed model to the Korean automobile market, and compare the fitting and forecasting performance with other Bass-type multi-product models.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.3 no.1
• /
• pp.110-118
• /
• 2011

This paper suggests a realistic, business engineers' model based on Coop projects run by regional universities or colleges, in which students must meet the guidelines for engineering design that ABEEK requires. Many of current activities such as Coop programs and Internships aimed for engineering majored-undergraduates have notled them either to a satisfactory level of business skill at entrepreneur side, or to their higher chance of employment opportunities. Under the circumstances like this, we need a revised version of Coop activities: for example, launching a project that will be fully supported intrust by both sides, and thus improving students' business skill while they are working on that project. We demonstrate in this study how students have greatly improved their business skill through a model project that was planned by a working group, was successfully carried out on real job positions, and many of the students in the working group were job-offered finally as this new model suggested.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.6
• /
• pp.747-752
• /
• 1999

In the fast sampling limit, the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper, we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that convers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control. The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.146-148
• /
• 2005

In this paper, we propose a genetically optimized identification of information granulation(IG)-based fuzzy model. To optimally design the IG-based fuzzy model we exploit a hybrid identification through genetic alrogithms(GAs) and Hard C-Means (HCM) clustering. An initial structure of fuzzy model is identified by determining the number of input, the seleced input variables, the number of membership function, and the conclusion inference type by means of GAs. Granulation of information data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the inital parameters are tuned effectively with the aid of the genetic algorithms and the least square method. And also, we exploite consecutive identification of fuzzy model in case of identification of structure and parameters. Numerical example is included to evaluate the performance of the proposed model.