• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.85-94
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• 2002

In this paper, we show that the 2nd-order iterative learning control algorithm with CITE is more effective and has better convergence performance than the algorithm without CITE in the case of the existence of initialization errors, for the trajectory-tracking control of dynamic systems with unidentified parameters. In contrast to other known methods, the proposed learning control scheme utilize more than one past error history contained in the trajectories generated at prior iterations, and a CITE term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances and initialization errors. And the convergence proof of the proposed algorithm in the case of the existence of initialization error is given in detail, and the effectiveness of the proposed algorithm is shown by simulation results.

• East Asian mathematical journal
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• v.25 no.2
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• pp.141-146
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• 2009

In this paper, we introduce a new generalized nonlinear quasivariational inequality and establish its equivalence with a xed point problem by using the resolvent operator technique. Utilizing this equivalence, we suggest two iterative schemes, prove two existence theorems of solutions for the generalized nonlinear quasivariational inequality involving generalized cocoercive mapping and establish some convergence results of the sequences generated by the algorithms. Our results include several previously known results as special cases.

• The Pure and Applied Mathematics
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• v.25 no.2
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• pp.149-160
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• 2018

In this paper, we prove a strong convergence result under an iterative scheme for N finite asymptotically $k_i-strictly$ pseudo-contractive mappings and a firmly nonexpansive mappings $S_r$. Then, we modify this algorithm to obtain a strong convergence result by hybrid methods. Our results extend and unify the corresponding ones in [1, 2, 3, 8]. In particular, some necessary and sufficient conditions for strong convergence under Algorithm 1.1 are obtained.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.325-336
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• 2008

In this paper, we prove the weak and strong convergence of the three-step iterative scheme with errors to a common fixed point for two asymptotically nonexpansive mappings in a uniformly convex Banach space under a condition weaker than compactness. Our theorems improve and generalize some previous results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.519-528
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• 1998

A numerical method is presented for the dynamic analysis of cam and follower. Contact and separation between the cam and the follower are analyzed by imposing dynamic contact condition. The correct solution is obtained without spurious oscillation by imposing the velocity and acceleration constraints as well as the displacement constraint on the possible contact point. The constraints are satisfied by iteratively reducing the constraint errors toward zero, and a simple time integration of ordinary differential equation is employed for the solution of the equation of motion. The solution procedure associated with the iterative scheme is presented, and numerical simulations are conducted to demonstrate the accuracy of the solution.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.585-592
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• 2003

Among various sensitivity evaluation techniques, semi-analytical method(SAM) is quite popular since this method is more advantageous than analytical method(AM) and global finite difference method(FDM). However, SAM reveals severe inaccuracy problem when relatively large rigid body motions are identified fur individual elements. Such errors result from the numerical differentiation of the pseudo load vector calculated by the finite difference scheme. In the present study, an iterative method combined with mode decomposition technique is proposed to compute reliable semi-analytical design sensitivities. The improvement of design sensitivities corresponding to the rigid body mode is evaluated by exact differentiation of the rigid body modes and the error of SAM caused by numerical difference scheme is alleviated by using a Von Neumann series approximation considering the higher order terms for the sensitivity derivatives.

• ETRI Journal
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• v.28 no.4
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• pp.435-443
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• 2006

This paper presents an efficient carrier recovery algorithm combined with a turbo-coding technique in a mobile communication system. By using a block turbo code made up of independently decodable block codes, we can efficiently recover the fast time-varying carrier phase as well as correct channel errors. Our simulation results reveal that the proposed scheme can accommodate mobiles with high speed, and at the same time can reduce the number of iterations to lock the phase.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.232-235
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• 1988

Recently, an iterative reconstruction-reprojection (IRR) algorithm has been suggested for application to incomplete data computed tomography (CT). In the IRR, the interpolation operation is performed in the image space during reconstruction-reprojection. The errors associated with the interpolation degrade the reconstructed image and may cause divergence unless a large number of rays is used. In this paper, we propose an improved IRR algorithm which eliminates the need for interpolation. The proposed algorithm adopts a new sampling scheme in which samples (projection data) is taken in phase with the samples of the Cartesian grid.