• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Steel and Composite Structures
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• v.26 no.1
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• pp.1-15
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• 2018

This study reported, the effect of random variation in system properties on bending response of single wall carbon nanotube reinforced composite (SWCNTRC) plates subjected to transverse uniform loading is examined. System parameters such as the SWCNT armchair, material properties, plate thickness and volume fraction of SWCNT are modelled as basic random variables. The basic formulation is based on higher order shear deformation theory to model the system behaviour of the SWCNTRC composite plate. A C0 finite element method in conjunction with the first order perturbation technique procedure developed earlier by the authors for the plate subjected to lateral loading is employed to obtain the mean and variance of the transverse deflection of the plate. The performance of the stochastic SWCNTRC composite model is demonstrated through a comparison of mean transverse central deflection with those results available in the literature and standard deviation of the deflection with an independent First Order perturbation Technique (FOPT), Second Order perturbation Technique (SOPT) and Monte Carlo simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.359-365
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• 2005

This paper presents an reduced-order near-optimal controller for the congestion control of Available Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks. We introduce the model, of a class of ABR traffic, that can be controlled using a Explicit Rate feedback for congestion control in ATM networks. Since there are great computational complexities in the class of optimal control problem for the ABR model, the near-optimal controller via reduced-order technique is applied to this model. It is implemented by the help of weakly coupling and singular perturbation theory, and we use bilinear transformation because of its computational convenience. Since the bilinear transformation can convert discrete Riccati equation into continuous Riccati equation, the design problems of optimal congestion control can be reduced. Using weakly coupling and singular perturbation theory, the computation time of Riccati equations can be saved, moreover the real-time congestion control for ATM networks can be possible.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.21-32
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• 2016

We study asymptotic expansion formulae for numerical computation of Greeks (i.e. sensitivity) in finance. Our approach is based on the integration-by-parts formula of the Malliavin calculus. We propose asymptotic expansion of Greeks for a stochastic volatility model using the Greeks formula of the Black-Scholes model. A singular perturbation method is applied to derive asymptotic Greeks formulae. We also provide numerical simulation of our method and compare it to the Monte Carlo finite difference approach.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.1-9
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• 2003

In the framework of linear perturbation theory and linear approximation of spacetime anisotropy, we investigated the formulae for the CMBR temperature anisotropy and fluctuation spectrum which have their origin in the primordial tensor perturbations of the perturbed Bianchi type I universe model. The resulting formulae were compared with those of the flat Friedmann model.

• Bulletin of the Korean Chemical Society
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• v.34 no.11
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• pp.3279-3283
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• 2013

We present an elementary pedagogical derivation of the Brillouin-Wigner and the Rayleigh-Schr$\ddot{o}$dinger perturbation theories with Epstein-Nesbet partitioning. A variant of the Brillouin-Wigner perturbation theory is also introduced, which can be easily extended to the quasi-degenerate case. A main advantage of the new theory is that the computing time required for obtaining the successive higher-order results is minimal after the third-order calculation. We illustrate the accuracy of the new perturbation theory for some simple model systems like the perturbed harmonic oscillator and the particle in a box.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.523-530
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• 2007

Crane systems are very important in industrial fields to carry heavy objects such that many investigations about control of the systems are actively conducted for enhancing its control performance. This paper presents an adaptive control approach using the model matching for a complex 3-DOF nonlinear crane system. First, the system model is linearized through feedback linearization method and then PD control is applied in the approximated model. This linear model is considered as nominal to derive corrective control law for a perturbed crane model using Lyapunov theory. This corrective control is primitively aimed to compensate real-time control deviation due to partially known perturbation. We additionally study stability analysis of the crane control system using Lyapunov perturbation theory. Evaluation of our control approach is numerically carried out through computer simulation and its superiority is demonstrated comparing with the classical control.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.41-48
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• 2014

Leak of liquid has been categorized conventionally into instantaneous release and continuous release. In this study, the spread of cryogenic liquid due to limited period of release is investigated for the first time to establish a new classification method with recognizing the irrationality of the conventional one. Such physical phenomena are governed by simultaneous equations concerning volume, radius and height of pool of the cryogenic liquid, and major parameters are evaporation rate per unit area, time of release, and spill quantity. The simultaneous governing equations is decoupled to get efficiently perturbation solutions. As the results, for the same spill quantity, in view of release model, combined release model that consists of continuous and consecutive instantaneous model is necessary with small time of release, while continuous model is solely required with large time of release. Also, the combined model is necessary for small spill quantity with the same time of release. These two regimes of release are clearly distinguished using the perturbation solution to provide a clear basis for the new classification of release models.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.277-286
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• 2002

Genetic programming (GP) has been combined with quantum mechanical perturbation theory to make a new algorithm to construct mathematical models and perform predictions for chaotic time series from real world. Procedural similarities between time series modeling and perturbation theory to solve quantum mechanical wave equations are discussed, and the exemplary GP approach for implementing them is proposed. The approach is based on multiple populations and uses orthogonal functions for GP function set. GP is applied to original time series to get the first mathematical model. Numerical values of the model are subtracted from the original time series data to form a residual time series which is again subject to GP modeling procedure. The process is repeated until predetermined terminating conditions are met. The algorithm has been successfully applied to construct highly effective mathematical models for many real world chaotic time series. Comparisons with other methodologies and topics for further study are also introduced.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.479-485
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• 2003

The influence of observations on the Wilks' lambda test of a linear hypothesis in multivariate regression is investigated using the local influence method. The perturbation scheme of case-weights is considered. A numerical example is given to show the effectiveness of the local influence method in identifying the influential observations.