• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.104-109
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• 2000

In this paper, the output feedback stabilizing problem is solved using any given state feedback control law. Compared to the linear systems is not so straightforward for nonlinear systems. We briefly explain the intrinsic obstructions for this problem and provide new output feedback scheme which achieves the semi-global stabilization with the high-gain state observer. THe overall uniform observability of the plant. Therefore, the result can be regarded as an extension of the separation principle for linear systems in some aspect.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.60-66
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• 1997

WE consider the stabilization of a class of multivariable nonlinear system using variable structure output feedback control. A high-gain observer is used to estimate state variable while rejecting the effect of the disturbances. We design a globally bounded output feedback variable structure controller that semi-globally stabilize the closed-loop system, while state variables do not exhibit a peaking.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.95-98
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• 1997

A nonlinear optical-microwave interaction is carried out in an uniplanar CPW-to-Slotline ring resonator on the semi-insulating GaAs substrate, in which a Schottky photodetector is monolithically integrated as a coupling gap. When the capacitive reactance of the detetor is modulated, the parametric amplification effect of the mixer occurs. In this device structure, the parametric amplification gain of 20 dB without the applied bias in RF signal is obtained. This microwave optoelectronic mixer can be used in the fiber-optic communication link.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.103-108
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• 1998

In this paper, we atempt to control the nonlinear power system for resistance spot welders to be a fully linearizesd system by applying the recently developed nonlinear feedback linearization techniques. the controller proposed in this paper is computationally simple. In addition, the easy gain tuning as well as the high dynamic performance of resistance spot welding systems can be obained simulaneously. To illustrate the dynamic performance of our controller further, we present some simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.4-40
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• 2001

This paper addresses the problem of designing robust adaptive output tracking control for a class of MIMO nonlinear systems which have different number of inputs and outputs The stability of the whole closed-loop system is guaranteed in the sense of Lyapunov and uniformly Itimately boundedness of the tracking error vector as well as estimated parameters are shown. In addition, we show that the restrictive assumptions on input gain matrix which is presumed in the past works can be eliminated by using proposed control law.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.451-457
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• 2015

In this paper, we consider the observer design problem that truly reflects the nonlinear stiffness of the manipulators. The two key ideas of our design are that (a) estimation error dynamics of the manipulator equipped with accelerometer dose not dependent on nonlinearities at the link part, when the measured signals are the motor position and the output of the accelerometer and (b) the nonlinear stiffness is indeed a Lipschitz function. In order to effectively compensate the nonlinear stiffness, the gain of the proposed observer is carefully chosen from the ARE(algebraic Riccati equations) which depend on Lipschitz constant. Comparative simulation result verifies the effectiveness of the proposed solution.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.468-474
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• 2005

Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.78-83
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• 2003

In this paper, it is dealt with a controller design problem for nonlinear systems with higher order relative degree. A robust adaptive control for uncertain nonlinear systems with stable zero dynamics will be proposed based on the high-gain adaptive output feedback and backstepping strategies. The proposed method is useful in the case where only the output signal is available.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.816-822
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• 2014

The estimation of the angular rate of a satellite has been discussed. A nonlinear observer has been proposed based on the state-dependent Riccati equation method. A sufficient stability condition for the convergence of estimation error has been presented. This condition is related to a state-dependent algebraic Riccati equation. It has been derived by transforming nonlinear error dynamics into a Lipschitz nonlinearity. An observer gain is obtained from this condition. Numerical simulations are presented to verify the proposed method.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.99-105
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• 1999

This paper presents a fuzzy H$\infty$ filtering problem for a class of uncertain nonlinear systems with time-varying delayed states and unknown inital state on the basis of Takagi-Sugeno(T-S) fuzzy model. The nonlinear systems are represented by T-S fuzzy models, and the fuzzy control systems utilize the concept of the so-called parallel distributed compensation. Using a single quadraic Lyapunov function, the stability and L2 gain performance from the noise signals to the estimation error are discussed. Sufficient conditions for the existence of fuzzy H$\infty$ filters are given in terms of linear matrix inequalities (LMIs). The filtering gains can also be directly obtained from the solutions of LMIs.