• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2099-2101
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• 2005

The problem of observer design for a class of Lipschitz nonlinear systems is considered. We propose a new observer design method which takes into account the structure of perturbed nonlinear terms with a scaling factor ${\epsilon}$. An example is provided to demonstrate the usefulness of our result over the existing method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.42.2-42
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• 2001

This paper deals with a fuzzy sliding mode observer for nonlinear systems. A nonlinear system is approximated by a multiple model Takagi Sugeno fuzzy system and then transformed into a canonical form for which a nonlinear observer is constructed. This study presents a type of fuzzy sliding mode observer that deals with matched and unmatched uncertainties in the plant dynamics very effectively. The proposed method was validated by the example of a inverted pendulum.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.837-841
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• 2008

This paper presents a robust reduced order state observer for a class of Lipschitz nonlinear systems with external disturbance. Sufficient conditions on the existence of the proposed observer are characterized by linear matrix inequalities. It is also shown that the proposed observer design can reduce the effect on the estimation error of external disturbance up to the prescribed level. Finally, a numerical example is provided to verify the proposed design method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.328-328
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• 2000

In this paper, An inverted pendulum system is typical of a nonlinear model. We propose a stable the inverted pendulum with fuzzy controller and state observer of nonlinear system. we represent the fuzzy system as a Takagj-Sugeno fuzzy model in addition, full-order state observer of inverted pendulum. As the result show fuzzy controller of inverted pendulum with nonlinear model of full-order state observer.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.189-194
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• 2002

This paper presents a state observer design for a class of MTMO nonlinear systems that has a block triangular structure. For this, the extension of the existing design for SISO triangular systems to MIMO cases is provided. Since the gain of the proposed observer. depends on a nonlinear part as well as a linear one of a system, it improves the transient performance of the high gain ob-server. Also, by using a generalized similarity transformation for the error dynamics, it is shown that order some boundedness condi-tion, the proposed observer guarantees the global exponential convergence of the estimation error. Finally, we will give a simulation example to show the validity of our design methodology.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.366-370
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• 1998

Indirect vector control for induction motors requires the use of observers for estimation or observation of rotor flux magnitude and position. In this paper, authors discribe the induction motor vector control and introduce a nonlinear observer, named ELO(extended Luenberger Observer), without simulation results as a preliminary work for trial application. Normally, design of nonlinear observer need coordinate transfromation and linearization through solving the partial different equation. However, ELO requires minimal solution of nonlinear partial differential equation. Simulation was performed by under the enviroment of Matlab and Simulink without the proposed observer because we are still working. Simulation was performed with conventional flux observer, a dc-ac inverter by SVPWM technique, a vector controller armed with multiple PI controllers

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.327-329
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• 2006

A controller is proposed for the robust adaptive backstepping control of a class of uncertain nonlinear systems using nonlinear disturbance observer (NDO). The NDO is applied to estimate the time-varying lumped disturbance in each step, but a disturbance observer error does not converge to zero since the derivative of lumped disturbance is not zero. Then the fuzzy neural network (FNN) is presented to estimate the disturbance observer error such that the outputs of the system are proved to converge to a small neighborhood of the desired trajectory. The proposed control scheme guarantees that all the signals in the closed-loop are semiglobally uniformly ultimately bounded on the basis of the Lyapunov theorem. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.296-304
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• 2002

A position tracking control schemes on the precise mechanical system in presence of nonlinear dynamic friction is proposed. A nonlinear dynamic friction is regarded as the bristle friction model to compensate effects of friction. The conventional sliding mode controller often has been used as a non-model-based friction controller, but it has a poor tracking performance in high-precision position tracking application since it completely cannot compensate the friction effect below a certain precision level. Thus to improve the precise position tracking performance, we propose the sliding mode control method combined with the friction-model-based observer having tunable structure of the transient response. Then this control scheme has a good transient response as well as the high precise tracking performance compared with the conventional sliding mode control without observer and the control system with similar type of observer. The experiments on the bali-screw drive table with the nonlinear dynamic friction show the feasibility of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1828-1832
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• 1991

We study the observer design problem for nonautonomous discrete-time nonlinear systems. We investigate the structure of nonautonomous discrete-time systems which are state equivalent to the nonlinear observer form and characterize their class. Necessary and sufficient conditions for the existence of an input independent (local) diffeomorphism axe derived which transforms multi-input, multi-output nonlinear systems into the nonlinear observer form.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.284-284
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• 2000

In adaptive fuzzy control systems. fuzzy systems are used to approximate the unknown plant nonlinearities. Until now. most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure based on system state availability. This paper considers observer-based nonlinear controller and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters for state observer and fuzzy rule structure are established so that the whole system is stable in the sense of Lyapunov.