• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.547-555
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• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.226-226
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• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1823-1831
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• 2011

When the RPS(Renewable Portfolio Standards) becomes effective in 2012, the use of renewable energy will be dramatically increased. However, there are no production simulations and demand supply programs that reflect the characteristics of the renewable energy. This paper analyzes correlations of the domestic wind power and solar power generation pattern in different areas and those of these sources' output and load pattern. Based on the regional correlation analysis, an appropriate method that uses a average output of the renewable energy or another modeling that takes account of uncertainty could be selected. Because it's output is dependent on weather condition, we can not control the generation of renewable energy, that is the reason why the correlation between the load and output pattern of sources can be helpful to determine whether the renewable energy is modeled as a generator or load modifier. Through this analysis, a basis will be provided in order to properly model the renewable energy source.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.705-711
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• 2013

In this paper, we introduce an design of multi-output fuzzy neural networks based on Interval Type-2 fuzzy set. The proposed Interval Type-2 fuzzy set-based fuzzy neural networks with multi-output (IT2FS-based FNNm) comprise the network structure generated by dividing the input space individually. The premise part of the fuzzy rules of the network reflects the individuality of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions with interval sets such as constant, linear, and modified quadratic inference for pattern recognition. The learning of fuzzy neural networks is realized by adjusting connections of the neurons in the consequent part of the fuzzy rules, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, uncertainty factor, learning rate and momentum coefficient were automatically optimized by using real-coded genetic algorithm. The proposed model is evaluated with the use of numerical experimentation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.3
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• pp.62-68
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• 2006

In this paper, an adaptive input-output linearization and zero dynamics control of three phase AC/DC converter are proposed. For achieving output do voltage regulation with unity power factor, the q-axis current of the rotating d-q frame is regulated to zero and the output do voltage is controlled to track a given reference voltage $V_r$. The proposed scheme is robust to the parametric uncertainty md load current of the converter due to the adaptation process. The simulation results are presented to illustrate the performance and feasibility of the proposed control scheme.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.1
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• pp.29-33
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• 2019

With shrinking form factor and improving performance of electronic packages, high input/output (I/O) density is considered as an important factor. Fan out wafer-level packaging (FO-WLP) has been paid great attention as an alternative. However, FO-WLP is vulnerable to warpage during its manufacturing process. Minimizing warpage is essential for controlling production yield, and in turn, package reliability. While many studies investigated the effect of process and design parameters on warpage using finite element analysis, they did not take uncertainty into consideration. As parameters, including material properties, chip positions, have uncertainty from the point of manufacturing view, the uncertainty should be considered to reduce the gap between the results from the field and the finite element analysis. This paper focuses on the effect of uncertainty of Young's modulus of chip on fan-out wafer level packaging warpage using finite element analysis. It is assumed that Young's modulus of each chip follows the normal distribution. Simulation results show that the uncertainty of Young's modulus affects the maximum von Mises stress. As a result, it is necessary to control the uncertainty of Young's modulus of silicon chip since the maximum von Mises stress is a parameter related to the package reliability.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.4
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• pp.436-442
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• 2011

To obtain the engine output correctly is basically very important factor for estimating a engine performance. But, it has been reported that the IHP measured from electronic indicator such as MIPS(Mean Indication Pressure System) has a deviation compared to mechanical indicator. It was reported by authors that the uncertainty of crank angle for TDC position could be one of the reasons. In this paper, the uncertainty of crank angle for TDC position and its influence to engine output were investigated respectively about M/E and G/E for marine diesel engines. For the purpose, two sampling methods of pressure in cylinder were considered which were 'angle base sampling' and 'time base sampling'. Angle base sampling is real crank angle acquired from angle encoder which is attached to crank shaft and time base sampling is crank angle calculated by detected revolution with Z-pluse of encoder. Time base sampling is same method of MIPS. This paper concluded that time base sampling method is not suitable for obtaining the output of marine diesel engine on board because of instantaneous speed variation and load fluctuation. Also it is verified that the variation of engine speed by load fluctuation should be one of reasons additionally in case of M/E.

• Journal of Korea Water Resources Association
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• v.38 no.4 s.153
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• pp.281-292
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• 2005

The water balance analysis for the long-term water resources plan is a simple calculation that compares water demands with possible water supplies. For a watershed being considered the reports on the performance of the water balance analysis, however, have shown inconsistent results and thus have not earned credibility due to the uncertainty of the data acquired and models used. In this research, uncertainties in the water scarcity estimate were assessed through probability representation based on the Monte Carlo simulation using Latin Hypercube Sampling (LHS). The natural flow, municipal demand, industrial demand, agricultural demand, and return flow rate were selected as representative input variables for the water balance analysis, and their distributions were set based on the linear regression and the entropy theory. The statistical properties of the output variable samples were analyzed in comparison with a deterministic estimate of the water scarcity of an existing study. Application of LHS to three sub-basins of the Geum river basin showed the deterministic estimate could be overestimated or underestimated. The sensitivity analysis as well as the uncertainty analysis found that the return flow rate of the agricultural water is the most uncertain but is rarely sensitive to the output of the water balance analysis.