• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.166-171
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• 2003

This paper presents the algorithms and Matlab Toolbox for co-simulation of distributed real-time control system based on OSEK-OS and CAN protocol. This toolbox enables the developers to analyze the timing uncertainty, which is caused by resource sharing including shared memories and networks, and to take the timing uncertainty into consideration in the early design phase. Furthermore, this toolbox helps the developers to model the behaviors of a control system by providing graphical user interface for objects of OSEK-OS and CAN. To prove the feasibility of this toolbox, a vehicle body network system is modeled with this toolbox, and the timing uncertainties are analyzed.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.325-332
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• 2010

A lens system for mobile phone cameras is comprised of various lenses and designed so as to satisfy design requirements for responses such as a modular transfer function (MTF). However, it is difficult to manufacture and assemble camera modules to maintain the same performance compared with the designed camera modules, because of uncertainty. We should always design a lens system by considering uncertainty that can be caused by errors in the manufacturing and assembly process of mobile phone cameras. The robust optimization offers tools of making robust decisions with the consideration of design parameters, uncontrollable parameters, and the variance of the system. Using an efficient reliability analysis method and an optimization algorithm, we obtained robust optimization results that maximize the mean of MTF and minimize the standard deviation and proposed a new robust design process for a lens system.

• Korean System Dynamics Review
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• v.11 no.3
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• pp.61-86
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• 2010

This research analyzed on the future energy society of Korea in 2030 using system thinking approach. Key uncertainty factors determining the future energy society were analyzed in a multi disciplinary view point such as politics, economy, society, ecology and technology. Three causal loop diagrams for the future energy system in Korea and related policy leverages were shown as well. 'Global economic trends', 'change of industrial structure' and 'energy price' were identified as key uncertainty factors determining the Korean energy future. Three causal loop diagrams named as 'rate of energy self－sufficiency and alternative energy production', 'economic activity and energy demand' and 'Excavation of new growth engines' were developed. We integrated those causal loop diagrams into one to understand the entire energy system of the future, proposed three strategic scenarios(optimistic, pessimistic and most likely) and discussed implications and limits of this research.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.1-14
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• 1996

Design of a reliable control systems is investigated for a class of uncertain linear plants. The uncertainty considered here is for the ase of uncertainty in the system matrix. A decentralized control scheme with two observer-based feedback controllers is developed, and it is shown that the resulting closed-loop system is reliable in the sense that the control scheme provides guaranteed stability and $H_{\infty}$-norm bounded performance in the event of sensor and/or actuator failures as well as in the presence of parameter uncertainties. We observed that soft-type failures were additional exogenous inputs to the closed-loop system. As a results, the sensor and/or actuator failures can be tolerated in the design, which is achieved by extending the methodology developed in.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2096-2098
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• 2001

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not be controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2116-2124
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• 2018

Magnetic levitation system with the advantages of non-contact, no friction and no wear can satisfy the requirement of high precision and high speed positioning. In this paper, magnetic levitation positioning stage which mainly consists of planar coil and HALBACH permanent magnet array and its control and driving system are designed. Magnetic levitation system is a highly nonlinear and strongly coupled complex system and its control performance can be influenced by the uncertainty and external disturbance. So exact feedback linearization method is used to realize exact linearization and decoupling, and a strategy of sliding mode control based on disturbance observer is proposed to compensate the uncertainty and external disturbance. Detailed proofs of observer's convergence property and system stability are derived. Both the simulation and experiment results verify the effectiveness of sliding mode control algorithm based on disturbance observer.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.405-412
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• 2020

The thermistor mount is used for precise RF power measurement because the calibration factor is constant according to the change of power. The calibration factor of the standard mount can be measured with an uncertainty less than 0.5 % from the 10 MHz to 1 GHz by direct comparison with the transfer standard using the DC substitution method. Recently, as the supply of precision power meter based on DC substitution method allows simple and fast measurement, a simple direct comparison measurement system with the same level uncertainty was designed and the minimum required specifications of components through analysis of mismatch error was proposed. The uncertainty was evaluated for system validation, and the results show that uncertainties have been well maintained within 0.5 % in the measurement frequencies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.935-942
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• 2018

Precipitation has a wide range of applications, such as the management and operation of dams and rivers, supply of dranking water for urban and industrial complex, farming and fishing, forest greening, and safety management. In order to prepare for disasters and to obtain economical effects in case of flood damage, it is necessary to measure accurate precipitation. In this study, we carried out the characteristics tests for various types of rainfall gauge using integrated verification system, which can analyze the performance of collective type rainfall gauge. The uncertainty for tipping bucket rain gauge was 0.0041 mm, where weight type and surface tension type was 0.0045 mm and 0.0039 mm respectively. Therefore, the uncertainty according to the type and characteristics of the precipitation system is not significantly different. The uncertainty is also influenced greatly by the resolution.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.568-580
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• 2020

Calibrating a conceptual hydrologic model necessitates selection of a calibration period that produces the most reliable prediction. This often must be chosen randomly, however, since there is no objective guidance. Observation plays the most important role in the calibration or uncertainty evaluation of hydrologic models, in which the key factors are the length of the data and the hydro-climate conditions in which they were collected. In this study, we investigated the effect of the calibration period selected on the predictive performance and uncertainty of a model. After classifying the inflows of the Hapcheon Dam from 1991 to 2019 into four hydro-climate conditions (dry, wet, normal, and mixed), a conceptual hydrologic partitioning model was calibrated using data from the same hydro-climate condition. Then, predictive performance and post-parameter statistics were analyzed during the verification period under various hydro-climate conditions. The results of the study were as follows: 1) Hydro-climate conditions during the calibration period have a significant effect on model performance and uncertainty, 2) calibration of a hydrologic model using data in dry hydro-climate conditions is most advantageous in securing model performance for arbitrary hydro-climate conditions, and 3) the dry calibration can lead to more reliable model results.