• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.395-401
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• 2004

By using an adaptive algorithm, together with an additional dynamic system, this paper proposes a new approach to design of a state observer for a class of uncertain systems. We enlarge the class of linear systems from the canonical form of [1] by proposing an adaptive observer that allows unknown parameters to affect those unmeasured states. The result is based on a recent result which presents a design algorithm for an additional system to replace output derivative measurements with the additional dynamics. A numerical example illustrates the design procedure of the state observer.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.383-388
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• 2007

This paper considers a low-order dynamic output feedback controller design problem. Since the proposed control law inherently has a low-pass filter property, it can alleviate the mal-effects of the sensor noise without additional filter designs. Frequency domain analysis shows the characteristics of the proposed control law against measurement noise. The effectiveness of the proposed control law is illustrated by numerical simulations with a rotary inverted pendulum and a convey-crane. Using only one integrator the proposed control law has the advantage to the stabilization problem with sensor noise as well as it can successfully replace the measurements of derivative terms in a state feedback control law.

• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.36-41
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• 2021

The motivation of this paper is to easily analyze the properties of nondispersive infrared gas sensor that has more than two different optical path length and to suggest the criterion and definition of infrared light absorbance in order to minimize the measurement errors. With the output voltage ratios and the normalized derivatives of infrared ray (IR) absorbance, when the normalized derivatives of IR absorbance decreases from 0.28 to 0.10, the lower and higher limits of errors were decreased from -5.62% and 2.39% to -4.27% and 2.78%. When the normalized derivatives of IR absorbance were 0.10, the output voltage could be partitioned into two regions with one exponential equation and the temperature compensation error was less than 5%.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.