• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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• pp.417-422
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• 2005

This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권5호
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• pp.315-322
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• 2004

A direct adaptive state-feedback controller for highly nonlinear systems is proposed. This paper considers uncertain or ill-defined nonaffine nonlinear systems and employs a static fuzzy logic system (FLS). The employed FLS estimates. and adaptively cancels an unknown plant nonlinearity using its proved universal approximation property. A control law and adaptive laws for unknown fuzzy parameters and bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov. The tracking error is guaranteed to be uniformly asymptotically stable rather than uniformly ultimately bounded with the aid of an additional robustifying control term. No a priori knowledge of an upper bound on an lumped uncertainty is required.

• Computers and Concrete
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• 제4권1호
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• pp.67-82
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• 2007

The discrete crack-concept is applied to study the 3D propagation of tensile-dominated failure in plain concrete. To this end the Partition of Unity Finite Element Method (PUFEM) is utilized and the strong discontinuity approach is followed. A consistent linearized implementation of the PUFEM is combined with a predictor-corrector algorithm to track the crack path, which leads to a robust numerical description of concrete cracking. The proposed concept is applied to study concrete failure during the PCT3D test and the predicted numerical results are compared to experimental data. The proposed numerical concept provides a clear interface for constitutive models and allows an investigation of their impact on concrete cracking under 3D conditions, which is of significant scientific interests to interpret results from 3D experiments.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.331-334
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• 1993

It is a standard problem that designs a controller to minimize the $H_{\infty}$-norm of a given plant. By reducing a standard problem to a model-matching problem, we can obtain all the parameters which consist of a controller. After presenting a practical model and applying it to a tracking model, we design an $H_{\infty}$ controller and an LQ controller to concrete that $H_{\infty}$ control theory is far more robust than LQ control theory. And we show the advantage of an $H_{\infty}$ controller by obtaining a desired Bode diagram and comparing it with that of an LQ controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1644-1645
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• 2007

This paper proposes an adaptive sliding mode control method for trajectory tracking of nonholonomic mobile robots with model uncertainties and external disturbances. The kinematic model represented by polar coordinates are considered to design a robust control system. Wavelet neural networks (WNNs) are employed to approximate arbitrary model uncertainties in dynamics of the mobile robot. From the Lyapunov stability theory, we derive tuning algorithms for all weights of WNNs and prove that all signals of an adaptive closed-loop system are uniformly ultimately bounded.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.1943-1945
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• 2001

In this paper, we present an adaptive output feedback control scheme for a class of uncertain nonlinear output-feedback form with time-varying parameters to which adaptive observer backstepping technique may not be applicable directly. In observer design, with the introduction of design function, we can deal with time-varying parameters in a very effective way. By the presented scheme, estimation error can be tuned to a desired small region around the origin via the design constants. Consequently, the observer with the presented design functions and the backstepping methodology achieve a robust regulation of the output tracking error while maintaining boundedness of all the signals and states.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.331-333
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• 1995

A high performance motor drive system must have a good speed command tracking, a insensitivity to a parameter variation and sampling time. In this paper, a robust speed controller for an induction motor is proposed. The speed controller is fuzzy-sliding adaptive controller and its system continuously is varied. That is, only P gain act in dynamic state, I gain in steady-state. Because this system is a sort of adaptive control system, global stability analysis is used to Lyapunov function. Consequently, in this paper application of fuzzy sliding adaptive controller to induction motor controlled by vecter control is presented and the control system is digitally implemented within DSP.

• Applied Science and Convergence Technology
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• 제25권5호
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• pp.98-102
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• 2016

The level set method has recently become popular in the simulation of semiconductor processes such as etching, deposition and photolithography, as it is a highly robust and accurate computational technique for tracking moving interfaces. In this research, full three-dimensional level set simulation has been developed for the investigation of focused ion beam processing. Especially, focused ion beam induced nanodot formation was investigated with the consideration of three-dimensional distribution of redeposition particles which were obtained by Monte-Carlo simulation. Experimental validations were carried out with the nanodots that were fabricated using focused $Ga^+$ beams on Silicon substrate. Detailed description of level set simulation and characteristics of nanodot formation will be discussed in detail as well as surface propagation under focused ion beam bombardment.

• 한국소음진동공학회논문집
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• 제19권2호
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• pp.169-175
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• 2009

This paper presents motion control of the Inchworm composed of the piezoelectric actuators and mechanical elements. Piezoelectric actuator shows nonlinear response characteristics including hysteresis due to the ferroelectric characteristics. This paper proposes feedback control scheme to improve the ability of tracking response to complex input signal and suppress the phenomenon of hysteresis using the sliding mode control technique with the integrator. The sliding mode control system has the limit to minimize both the settle time and overshoot. For making up this limit, this paper also suggests input shaping technique suitable to the inchworm control system.