• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.580-583
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• 2003

The general time optimal control law provides the optimal solution for a minimum time control problem. But in most real systems with disturbances and model uncertainties, the time optimal control law leads to chattering effect. This chattering effect can cause the system to be unstable. Therefore, we propose a robust optimal control algorithm for the nonlinear second order systems with model uncertainty. The proposed algorithm is combined with bang-bang control and sliding mode control. Thus the proposed algorithm has two state space regions to implement to control algorithm. In each region, the appropriate linear or nonlinear feedback control law is used satisfying the dynamic system equations. Simulation results show the superiority of the proposed controller in comparison with pure time optimal control(bang-bang control).

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.138-144
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• 2000

Robot manipulators, which are nonlinear structures and have uncertain system parameters, have complex in dynamics when are operated in unknown environment. To compensate for estimate errors of the uncertain system parameters and to accomplish the desired trajectory tracking, nonlinear robust controllers are appropriate. However, when estimation errors or tracking errors are large, they require large input torques, which may not be satisfied due to torque limits of actuators. As a result, their stability can not be guaranteed. In this paper, a new robust control scheme is presented to solve stability problem and to achieve fast trajectory tracking in the presence of torque limits. By using fuzzy logic, new desired trajectories which can be reduced are generated based on the initial desired trajectory, and torques of the robust controller are regulated to not exceed torque limits. Numerical examples are shown to validate the proposed controller using an uncertain two degree-of-freedom underwater robot manipulator.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.357-361
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• 2007

This paper presents a multi-robot localization based on Bayesian Multidimensional Scaling (BMDS). We propose a robust MDS to handle both the incomplete and noisy data, which is applied to solve the multi-robot localization problem. To deal with the incomplete data, we use the Nystr${\ddot{o}}$m approximation which approximates the full distance matrix. To deal with the uncertainty, we formulate a Bayesian framework for MDS which finds the posterior of coordinates of objects by means of statistical inference. We not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

• Earthquakes and Structures
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• v.13 no.6
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• pp.599-611
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• 2017

This paper improves seismic fragility of a typical steel-concrete composite bridge with the deck-to-pier connection joint configuration at the concrete crossbeam (CCB). Based on the quasi-static test on a typical steel-concrete composite bridge model under the SEQBRI project, the damage states for both of the critical components, the CCB and the pier, are identified. The finite element model is developed, and calibrated using the experimental data to model the damage states of the CCB and the bridge pier as observed from the experiment of the test specimen. Then the component fragility curves for both of the CCB and the pier are derived and combined to develop the system fragility curves of the bridge. The uncertainty associated with the mean system fragility has been discussed and quantified. The study reveals that the CCB is more vulnerable than the pier for certain damage states and the typical steel-concrete composite bridge with CCB exhibits desirable seismic performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.113-119
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• 2006

The importance of intellectual property is increasing in the knowledge and information era. An organization that embraces technology and strategy is faced with promising opportunities and managerial difficulties. Forecasting the performance of technology and the underlying costs to achieve such performance is even more difficult than before. Those organizations that employ technology as part of their strategic arsenal know that they are running serious risks, which clearly increases the uncertainty of organizational performance. Therefore forecasting the performance of technology is a difficult task since technology has been characterized by intangible and tacit factors and traded in a supplier's market. The decision makers usually face a complex system of interrelated components, such as resources, desired outcomes or objectives. This study intends to evaluate the contribution of technology in intangible assets by the Analytic Hierarchy Process.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.244-250
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• 1996

Uncertainties in core neutronic calculations of CASMO-3/MASTER, which is a KAERI developed core nuclear design code system, were evaluated via comparisons with measured data. Comparisons were performed with plant measurement data from one Westinghouse type and one ABB-CE type plant and two Korean standard type plants. The CASMO-3/MASTER capability and levels of accuracy are concluded to be sufficient for the neutronics design including safety related parameters related with reactivity, power distributions, temperature and power coefficients, inverse boron worth and control bank worth.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.163-169
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• 2019

The robust controller synthesis and analysis of the water level process in the U-tube system generator (UTSG) is addressed in this paper. The parameter uncertainties of the steam generator (SG) are modeled as multiplicative perturbations which are normalized by designing suitable weighting functions. The relative errors of the nominal SG model with respect to the other operating power level models are employed to specify the weighting functions for normalizing the plant uncertainties. Then, a robust controller is designed based on ${\mu}$-synthesis and D-K iteration, and its stability robustness is verified over the whole range of power operations. A gain-scheduled controller with $H_{\infty}$-synthesis is also designed to compare its robustness with the proposed controller. The stability analysis is accomplished and compared with the previous QFT design. The ${\mu}$-analysis of the system shows that the proposed controller has a favorable stability robustness for the whole range of operating power conditions. The proposed controller response is simulated against the power level deviation in start-up and shutdown stages and compared with the other concerning controllers.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1412-1420
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• 2018

An experiment was performed using the large-scale test facility (LSTF), which simulated a 1% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under an assumption of total-failure of high-pressure injection (HPI) system in a pressurized water reactor (PWR). In the LSTF test, liquid level in the upper head affected break flow rate. Coolant was manually injected from the HPI system into cold legs as the AM measure when the maximum core exit temperature reached 623 K. The cladding surface temperature largely increased due to late and slow response of the core exit thermocouples. The AM measure was confirmed to be effective for the core cooling. The RELAP5/MOD3.3 code indicated insufficient prediction of primary coolant distribution. The author conducted uncertainty analysis for the LSTF test employing created phenomena identification and ranking table for each component. The author clarified that peak cladding temperature was largely dependent on the combination of multiple uncertain parameters within the defined uncertain ranges.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.151.5-151
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• 2001

Sliding mode control is investigated for a discrete-time system with uncertainties. The narrowest neighborhood of the sliding surface is shown in which the state can remain. The range is determined by the upper bound of the absolute value of the uncertainty and the equation of the sliding surface. A sliding mode control algorithm is proposed to keep the state there without requiring an enormous input. Under the presence of the system parameter variations, the origin is not always stable although the sliding surface represents the stable dynamics and the state is kept in this neighborhood. The condition for the origin to be stable is investigated. Furthermore, the problems occurring when a continuous-time sliding mode control being ...

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.118-125
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• 1997

Non-contacting optical microscopes are increasingly used in recent industrial applications of probes for coordinate measuring machines. They have been found more efficient than conventional touch trigger porbes with ball tips especially in inspecting small-sized objects. There are two major factors affecting measuring accuracy: (1) geometric relations between coordinate systems, (2) magnification ratios of a microscope. In order to determine the magnification ratios exactly, optical imaging of edge was theroretically analyzed and practically adopted to image processing for edge detection. In addition, this paper proposes a geometric calibration method to obtain exact coordinates of measured points from the relations between the machine coordinate system and the image. In the method, the error according to the squareness between the machine axises was also removed. The method was practically adopted to a real coordinate measuring machine. An ultraprecision measurement of 0.2 um uncertainty can be practically achieved.