• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.33-55
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• 2005

The temporal discretisation of a moderate semilinear parabolic problem in an abstract setting by the two-step backward differentiation formula with variable step sizes is analysed. Stability as well as optimal smooth data error estimates are derived if the ratios of adjacent step sizes are bounded from above by 1.91.

• The Journal of Natural Sciences
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• v.8 no.1
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• pp.5-15
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• 1995

The equation error formulation in the adaptive IIR filtering provides convergence to a global minimum regardless a local minimum with a large stability margin. However, the equation error formulation suffers from the bias in the coefficient estimates. In this paper, a new algorithm, which does not require a prespecification of the noise variance, is proposed for the equation error formulation. This algorithm is based on the equation error smoothing and provides an unbiased parameter estimate in the presence of white noise. Through simulations, it is demonstrated that the algorithm eliminates the bias in the parameter estimate while retaining good properties of the equation error formulation such as fast convergence speed and the large stability margin.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.27-43
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• 2002

Finite element Galerkin solutions for the strongly damped extensible beam equations are considered. The semidiscrete scheme and a fully discrete time Galerkin method are studied and the corresponding stability and error estimates are obtained. Ratios of numerical convergence are given.

• Bulletin of the Korean Mathematical Society
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• v.47 no.6
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• pp.1225-1234
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• 2010

Numerical solutions for the fractional differential dispersion equations with nonlinear forcing terms are considered. The backward Euler finite difference scheme is applied in order to obtain numerical solutions for the equation. Existence and stability of the approximate solutions are carried out by using the right shifted Grunwald formula for the fractional derivative term in the spatial direction. Error estimate of order $O({\Delta}x+{\Delta}t)$ is obtained in the discrete $L_2$ norm. The method is applied to a linear fractional dispersion equations in order to see the theoretical order of convergence. Numerical results for a nonlinear problem show that the numerical solution approach the solution of classical diffusion equation as fractional order approaches 2.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1991-2000
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• 2017

This paper presents a compensative microstepping based position control with passive nonlinear adaptive observer for permanent magnet stepper motor. Due to the resistance uncertainties, a position error exists in the steady-state, and a ripple of position error appears during operation. The compensative microstepping is proposed to remedy this problem. The nonlinear controller guarantees the desired currents. The passive nonlinear adaptive observer is designed to estimate the phase resistances and the velocity. The closed-loop stability is proven using input to state stability. Simulation results show that the position error in the steady-state is removed by the proposed method if the persistent excitation conditions are satisfied. Furthermore, the position ripple is reduced, and the Lissajou curve of the phase currents is a circle.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.72-81
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• 2009

This paper presents a robust adaptive control method using model reference control strategy against autonomous robot systems with random friction nature. We approximate a nonlinear robot system model by means of a feedback linearization approach to derive nominal control law. We construct a Least Square (LS) based observer to estimate friction dynamics online and then represent a perturbed system model with respect to approximation error between an actual friction and its estimation. Model reference based control design is achieved to implement an auxiliary control in order for reducing control error in practice due to system perturbation. Additionally, we conduct theoretical study to demonstrate stability of the perturbed system model through Lyapunov theory. Numerical simulation is carried out for evaluating the proposed control methodology and demonstrating its superiority by comparing it to a traditional nominal control method.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1205-1219
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• 2011

In this work, a stabilized characteristic finite volume method for the time-dependent Navier-Stokes equations is investigated based on the lowest equal-order finite element pair. The temporal differentiation and advection term are dealt with by characteristic scheme. Stability of the numerical solution is derived under some regularity assumptions. Optimal error estimates of the velocity and pressure are obtained by using the relationship between the finite volume and finite element methods.

• Geomechanics and Engineering
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• v.31 no.4
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• pp.339-352
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• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• Journal of the Korean Mathematical Society
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• v.44 no.6
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• pp.1281-1290
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• 2007

We introduce three spectral regularization methods for solving a backward heat conduction problem (BHCP). For the three spectral regularization methods, we give the stability error estimates with optimal order under an a-priori and an a-posteriori regularization parameter choice rule. Numerical results show that our theoretical results are effective.

• Journal of the Korean Mathematical Society
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• v.51 no.4
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• pp.665-678
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• 2014

We present a new space-time discontinuous Galerkin (DG) method for solving the time dependent, positive symmetric hyperbolic systems. The main feature of this DG method is that the discrete equations can be solved semi-explicitly, layer by layer, in time direction. For the partition made of triangle or rectangular meshes, we give the stability analysis of this DG method and derive the optimal error estimates in the DG-norm which is stronger than the $L_2$-norm. As application, the wave equation is considered and some numerical experiments are provided to illustrate the validity of this DG method.