• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.22-31
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• 1999

In this paper, a robust observer design method for nonlinear multi input multi-output(MINO) plants is presented. This method enables the extension of the time delay observer (TDO) for nonlinear SISO plants in the phase variable form to MIMO plants. The designed TDO reconstructs the states of the plant expressed in the generalized observability canonical form (GOBCF), yet requiring neither the transformation of a plant, nor the real time computation coordinates, the observer turned out to be computationally efficient and easy to design for nonlinear MIMO plants. In a simulation of a two-link manipulator with flexible joints, the control performances using TDO appeared to be similar to those using actual states and superior to those using numerical differentiation. Finally, in an experiment with a robot, it was confirmed that the TDO reconstructs the states reliability and TDO can be effectively used in a real closed-loop system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.126-131
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• 2015

Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1823-1827
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• 1991

The problem regarding nonlinear systems has come to occupy an important position. In order to solve a nonlinear problem we have methods of linearization which are developed through linear approximation to adapt linear system theories. In this paper we present a formal linearization of nonlinear systems based on the discrete-Fourier transform (D.F.T.).

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.141-144
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• 1999

The authors have recently developed a new method for identification of Volterra kernels of nonlinear systems by use of pseudorandom M-sequence and correlation technique. And it is shown that nonlinear systems which can be expressed by Volterra series expansion are well identified by use of this method. However, there exist many nonlinear systems which can not be expressed by Volterra series mathematically. A nonlinear system having backlash type nonliear element is one of those systems, since backlash type nonlinear element has multi-valued function between its input and output. Since Volterra kernel expression of nonlinear system is one of the most useful representations of non-linear dynamical systems, it is of interest how the method of Volterra kernel identification can be ar plied to such backlash type nonlinear system. The authors have investigated the effect of application of Volterra kernel identification to those non-linear systems which, accurately speaking, is difficult to express by use of Volterra kernel expression. A pseudorandom M-sequence is applied to a nonlinear backlash-type system, and the crosscorrelation function is measured and Volterra kernels are obtained. The comparison of actual output and the estimated output by use of measured Volterra kernels show that we can still use Volterra kernel representation for those backlash-type nonlinear systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.203-206
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• 2002

This paper describes fuzzy control methodologies of the steam generator which have nonlinear characteristics in the nuclear power plant. Actually, the steam generator part of the power generator has a problem to control water level because it has complex components and nonlinear characteristics. In order to control nonlinear terms of the model, Takagj-Sugeno (75) fuzzy system is used to design a controller. In designing procedure, intelligent digital redesign method is used to control the nonlinear system. This digital controller keeps the performance of the analog controller. Simulation examples are included for ensuring the proposed control method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.315-317
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• 2006

In this paper, we design a terminal sliding mode controller based on neural network for nonlinear systems with uncertainties. Terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time. Also, TSMC has the advantages such as improved performance, robustness, reliability and precision by contrast with classical sliding mode control. For the control of nonlinear system with uncertainties, we employ the self-recurrent wavelet neural network(SRWNN) which is used for the prediction of uncertainties. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out simulations to illustrate the effectiveness of the proposed control.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.406-409
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• 2000

We propose the modified neural network which are paralleled to control nonlinear systems. The proposed method is a direct control method to use inverse model of the plant. Nonlinear systems are divided into two parts; linear part and nonlinear part, and it is controlled by RLS method and recursive multi-layer neural network with each other. We simulate to verify the performance of the proposed method and are compared with conventional direct neural network control method. The proposed control method is improved the control performance than the conventional method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.666-671
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• 2017

A disturbance-observer-based adaptive neural tracker design problem is investigated for a class of perturbed uncertain non-affine nonlinear systems with unknown control direction. A nonlinear disturbance observer (NDO) design methodology using neural networks is presented to construct a tracking control scheme with the attenuation effect of an external disturbance. Compared with previous control results using NDO for nonlinear systems in non-affine form, the major contribution of this paper is to design a NDO-based adaptive tracker without the sign information of the control coefficient. The stability of the closed-loop system is analyzed in the sense of Lyapunov stability.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.684-688
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• 1996

In this paper, to overcome drawbacks of variable structure control system a self-tuning fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to a one-degree of freedom robot arm. The results show that both alleviation of chattering and performance are achieved.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.363-367
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• 1996

In general, the physiological systems have shown nonlinear complex phenomena. This study analyzes nonlinear characteristics of the flow of peripheral blood vessel dynamics in physiological systems using chaos theory. We performed this study by means of several quantity methods and power spectrum. The quantity methods are a phase space reconstruction and a poincare's map. And the power spectrum method is a conventional linear analysis. Experimental data have been acquired from examining 10 diabetic patients, and 10 control subjects in initial stable state. In acquisition experminetal data, we anlysized the differences of nonlinear characteristics between diabetic group and control group. The results of quality analysis methods showed the flow of peripheral blood vessel had the nonlinear and chaotic characteristics, screening a strange attractor on reconstructed phase space. In conclusion, the flow dynamics of peripheral blood vessel had a chaotic behavior of nonlinear dynamic systems, dynamic system, and differences of characteristic of nonlinear dynamic system.