• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.83.5-83
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• 2002

Perspective dynamical systems arise in machine vision, in which only perspective observation is available, and the essential problem is to estimate the state and /or unknown parameters for a moving rigid body based on the observed information. This paper proposes and studies a Luenberger-type observer for perspective tim e-varying linear systems. In particular, assuming a given perspective time-varying linear system to be Lyapunov stable and to satisfy some sort of observability condition, it is shown that the estimation error converges exponentially to zero. Finally, a simple numerical exam pie is presented to illustrate the result obtained.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.370-377
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• 2000

This paper presents a decentralized compensator design procedure for large scale systems. By using a coordinate transformation method, interconnection terms in t도 subsystem are decoupled and a decentralized observer is designed independently as a form of Luenberger-type for each subsystem. And the decentralized compensator which can select the observer and controller gain independently is designed as a form of observer based controller for each subsystem. The proposed method has a simplicity and conciseness in the aspects of the determination of coordinate transformation matrices and the derivation of the separation principle which is adopted independently for each subsystem.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.480-485
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• 2005

Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.59-62
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• 2010

로봇모터제어에 사용되는 서보전동기의 센서리스 운전에 대한 초기의 연구에서는 전동기의 전압과 전류를 측정하여 전동기 모델로부터 속도를 연산하는 방식을 취해왔으나, 근래에는 현대제어 이론 중 관측기 이론을 적용하여 속도 추정 및 센서리스 운전을 위한 다양한 연구가 시도되고 있다. 본 논문에서 설계한 슬라이딩형 퍼지 관측기의 속도추정 성능을 검증하기 위해 먼저 슬라이딩 관측기를 이용하여 전기자 전류의 도함수를 추정하고 속도관측기인 Luenberger 관측기의 이득을 퍼지 제어 기법을 이용하여 관측기 이득을 최적 값으로 선정하고 이것을 이용하여 직류 서보 전동기의 속도제어에 적용하였다.

• Journal of Power Electronics
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• v.12 no.4
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• pp.604-614
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• 2012

This paper presents a comparative study of position sensorless control schemes based on back-electromotive force (back-EMF) estimation in permanent magnet synchronous motors (PMSM). The characteristics of the estimated back-EMF signals are analyzed using various mathematical models of a PMSM. The transfer functions of the estimators, based on the extended EMF model in the rotor reference frame, are derived to show their similarity. They are then used for the analysis of the effects of both the motor parameter variations and the voltage errors due to inverter nonlinearity on the accuracy of the back-EMF estimation. The differences between a phase-locked-loop (PLL) type estimator and a Luenberger observer type estimator, generally used for extracting rotor speed and position information from estimated back-EMF signals, are also examined. An experimental study with a 250-W interior-permanent-magnet machine has been performed to validate the analyses.