• Korean Journal of Computational Design and Engineering
• /
• v.5 no.4
• /
• pp.319-326
• /
• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

• Journal of Institute of Control, Robotics and Systems
• /
• v.1 no.2
• /
• pp.88-93
• /
• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• Smart Structures and Systems
• /
• v.19 no.4
• /
• pp.431-439
• /
• 2017

This investigation is aimed to develop a model of experimental-computation determination of a support moment of a cantilever beam loaded with concentrated force at its end including the optimal choice of coordinates of deflection data points and parameters of transformation of deflection data in case of insufficient accuracy of the assignment of initial parameters (support settlement, angle of rotation of the bearing section) and cantilever beam length. The influence of distribution and characteristics of sensors on the cantilever beam on the accuracy of determining the support moment which improves in the course of transition from the uniform distribution of sensors to optimal non-uniform distribution is shown. On the basis of the theory of inverse problems the method of transformation reduction at numerical differentiation of deflection functions has been studied. For engineering evaluation formulae of uncertainty estimate to determine a support moment of a cantilever beam at predetermined uncertainty of measurements using sensors have been obtained.

• International Journal of Fluid Machinery and Systems
• /
• v.2 no.4
• /
• pp.278-285
• /
• 2009

Operational modal analysis (OMA) allows modal parameters, such as natural frequencies and damping, to be estimated solely from data collected during operation. However, a main shortcoming of these methods resides in the evaluation of the accuracy of the results. This paper will explore the uncertainty and possible variations in the estimates of modal parameters for different operating conditions. Two algorithms based on the Least Square Complex Exponential (LSCE) method will be used to estimate the modal parameters. The uncertainties will be calculated using a Monte-Carlo approach with the hypothesis of constant modal parameters at a given operating condition. In collaboration with Andritz-Hydro Ltd, data collected on two different stay vanes from an Andritz-Hydro Ltd Francis turbine will be used. This paper will present an overview of the procedure and the results obtained.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.272-272
• /
• 2000

since the controller is part or the overall closed-Loop system, it is necessary that the designed controller be able to tolerate some uncertainty in its coefficients. The adequate stability and performance margins are required for the designed nominal controllers. In the paper. we study the method to design the non-fragile fixed-structured controller for real parametric uncertain systems. When we impose the controller parameter perturbation, the structure of the controller must be given. Therefore, we assume that the controller has fixed-structure. The fixed-structure controller is practically necessary especially when the robust controller synthesis results in a high-order controller. In SISO systems, we propose the robust controller design method using the Mapping theorem. In the method, the plant uncertainty and controller Parameter are of the multilineal form in the stability and performance conditions. Then, the controller synthesis problem is easily recast to Linear Programming Problem.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.6
• /
• pp.166-175
• /
• 1999

This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.2840-2853
• /
• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.36 no.3
• /
• pp.61-74
• /
• 2011

The objective of this study is to evaluate the effects of sharing uncertain yield information with a downstream supply chain player. We are interested in understanding how the amount of yield uncertainty affects the supply-side benefits and/or costs, which has not been considered in the literature, in addition to the customer-side benefits. With that purpose, this work evaluates a supplier who provides yield information in comparison with another supplier who shares no information. We simulate an order-up-to type heuristic policy that is adapted from the literature and reasonably modified to represent yield information sharing with error. From the simulation study, we argue that the customer would experience cost reduction, but the cost for supplier's inventory is increasing when sharing yield information. Furthermore, the amount of benefits and costs are situational and affected by level of yield uncertainty and demand variance. Based on the simulation study, we finally make several recommendations for the supply-side approaches to yield information sharing.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.12 no.11
• /
• pp.1012-1019
• /
• 2000

A proficiency test is one of programs which Korea Research Institute of Standards and Science(KRISS), as national metrology institute, is putting in operation for the mutual recognition arrangement. The Fluid Flow Group of KRISS evaluated the measurement capability for liquid flowmeter calibrator of the national calibration and test organizations. The uncertainty of national standard system was estimated in accordance with Guide to The Expression of Uncertainty in Measurement (ISO), and the turbine flowmeter, which was used for the round-robin test as a reference flowmeter, was characterized. The round-robin tests with the turbine flowmeter package were carried out in 1995 and 1999. The test results of the organizations and those of KRISS agreed within $\pm0.2$%. It is found thus that the organizations have the traceability of the national standard for liquid flow measurement.

• Journal of Institute of Control, Robotics and Systems
• /
• v.1 no.1
• /
• pp.20-24
• /
• 1995

In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.