• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1146-1151
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• 2003

In this paper, results of an analysis of driving behavior characteristics and a driver-adaptive control algorithm for adaptive cruise control systems have been described. The analysis has been performed based on real-world driving data. The vehicle longitudinal control algorithm developed in our previous research has been extended based on the analysis to incorporate the driving characteristics of the human drivers into the control algorithm and to achieve natural vehicle behavior of the adaptive cruise controlled vehicle that would feel comfortable to the human driver. A driving characteristic parameters estimation algorithm has been developed. The driving characteristics parameters of a human driver have been estimated during manual driving using the recursive least-square algorithm and then the estimated ones have been used in the controller adaptation. The vehicle following characteristics of the adaptive cruise control vehicles with and without the driving behavior parameter estimation algorithm have been compared to those of the manual driving. It has been shown that the vehicle following behavior of the controlled vehicle with the adaptive control algorithm is quite close to that of the human controlled vehicles. Therefore, it can be expected that the more natural and more comfortable vehicle behavior would be achieved by the use of the driver adaptive cruise control algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.11
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• pp.2932-2943
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• 1994

An efficient approach to the automatic construction of effective quadrilateral finite element meshes for two-dimensional analysis is presented. The procedure is composed of, firstly, an initial mesh generation and, secondly, an h-version of adaptive refinement based on error analysis. As for an initial mesh generation scheme, a modified looping algorithm has been employed. For the adaptive refinement process, an error indicator obtained by computing the residual error of the equilibrium equations in the energy norm with a relaxation factor has been employed. Examples of mesh generation and self-adaptive mesh improvements are given. These example solutions demonstrate that an effective mesh for a given error tolerance can be obtained in a few steps of the analysis processes.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.305-311
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• 2003

We propose a new technique of adaptive-neuro controller design to implement real-time control of robot manipulator, Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of loaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real time control of robot system using DSPs(TMS320C50)

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.19-29
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• 2019

This paper analyzes the design factors for GNSS anti-jamming receiver system in which the adaptive beamforming algorithm is applied in GNSS receiver system. The design analysis factors used in this paper are divided into three: antenna, beamforming algorithm, and operation environment. This paper analyzes the above three factors and presents numerical simulation results on antenna and beamforming algorithm.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.5 s.236
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• pp.568-576
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• 2005

A 3-D finite element model combined with a volume tracking method is presented in this work to simulate the mold filling for casting processes. Especially, the analysis involves an adaptive grid method that is created under a criterion of element categorization of filling states and locations in the total region at each time step. By using an adaptive grid wherein the elements, finer than those in internal and external regions, are distributed at the surface region through refinement and coarsening procedures, a more efficient analysis of transient fluid flow with free surface is achieved. Adaptive grid based on VOF method is developed in tetrahedral element system. Through a 3-D analysis of the benchmark test of the casting process, the efficiency of the proposed adaptive grid method is verified. Developed FE code is applied to a typical industrial part of the casting process such as aluminum road wheel.

• Structural Engineering and Mechanics
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• v.6 no.1
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• pp.115-124
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• 1998

A novel boundary stress resolution method is suggested in this paper, which is based upon the displacements of finite element analysis and of high precision with stress boundary condition strictly satisfied. The method is used to modify the Zienkiewicz-Zhu ($Z^2$) a posteriori error estimator and for the h-version adaptive finite element analysis of crack problems. Successful results are obtained.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.447-455
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• 1999

An adaptive mesh generation scheme is developed for effective non-linear analysis of the shell structures under large deformation. In particular, based on a posteriori error estimation, remeshing method on each load step is of primary interest here. An advancing front method, called paving method, is adopted for remeshing. It can be known that the adaptive mesh generation using contours of spacing values obtained from stress errors has an advantage in the adaptive analysis of the shell structures.