• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.171-176
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• 2004

Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

• 한국조명전기설비학회지:조명전기설비
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• 제9권4호
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• pp.55-61
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• 1995

Variable structure control (VSC) can be used for the control of power plants required stability and robustness such as elevator control. It has no overshoot and is insensitive to parameter variations and disturbances in the sliding mode where the system structure is changed with the sliding surface in the center. But in the real system, VSC has a high frequency chattering which has a bad influence upon the control system proformances. In this paper, to alleviate the high frequency chattering, a binary controller (BC) with inertial type external loop is implemented by DSP and applied to position control of brushless DC motor. Binary controller has external loop to generate the continuous control input with the flexible variation of primary loop gain. Thus it has the property of chattering alleviation in addition to advantages of the conventional variable structure control.

• Steel and Composite Structures
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• 제14권1호
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• pp.57-71
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• 2013

The prediction of the low cycle fatigue (LCF) life of beam-column connections requires an LCF model that is developed using specific geometric information. The beam-column connection has several geometric variables, and changes in these variables must be taken into account to ensure sufficient robustness of the design. Previous research has verified that the finite element model (FEM) can be used to simulate LCF behavior at the end plate moment connection (EPMC). Three critical parameters, i.e., end plate thickness, beam flange thickness, and bolt distance, have been selected for this study to determine the geometric effects on LCF behavior. Seven FEMs for different geometries have been developed using these three critical parameters. The finite element analysis results have led to the development of a modified LCF model for the critical parameter groups.

• 대한기계학회논문집A
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• 제20권3호
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• pp.843-849
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• 1996

The least square estimation is used frequently in experimental modal analysis techinque to eliminate noise signals. However, identified modal parameters are sometimes inaccurate, since the least squre estimation is sensitive to noise. In this paper, a new total least squre estimation, which is robust to noise signals, is developed and applied to experimental modal analysis technique such as Prony method and Circle Fit method. Several simulated results show that the proposed method is robuster to noise than conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.99-102
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• 1996

A novel iterative learning control scheme comprising a unique feedforward learning controller and a disturbance observer is proposed. Disturbance observer compensates disturbance due to parameter variations, mechanical nonlinearities, unmodeled dynamics and external disturbances. The convergence and robustness of the proposed controller is proved by the method based on Lyapunov stability theorem. The results of numerical simulation are shown to verify the effectiveness of the proposed control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.24.1-24
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• 1996

The development of future aircraft that involves the expanded flight envelop will place increased performance requirements on the design of the flight control system. Maneuvering areas are expanding into flight envelopes characterized by significantly larger levels of modeling uncertainty than encountered in present flight control designs. Conventional flight control techniques that ignore the effects of large parameter variations, modeling uncertainties and nonlinearities, will likely produce designs with poor performance and robustness. Recent advances in modern control theories called advanced control theories, most notably the H$\_$.inf./ synthesis technique, adaptive control and neural network application, offer the promise of a design technique that can produce both high performance and robust controllers for next generation aircraft. This special lecture will survey the recent development in advanced flight control and review the possible application of advanced control theories.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.143-146
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• 1997

In this paper, we propose a fuzzy-supervised nonlinear H$_{\infty}$ controller which guarantees the robustness and has exact tracking performance for robot manipulator with system parameter uncertainty and exogenous disturbance, The proposed controller which is based on robotic H$_{\infty}$ controller has fuzzy supervisor which decides the optimal control input weighting value through fuzzy making-decision process. Owing to the fuzzy supervisor, The proposed controller can take the optimal control input. Then, we will apply the proposed controller to rigid robot manipulator to verify the performance of our controller.r.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.565-569
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• 2003

In this paper, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system with an integral quadratic constraint. We also derive the important characteristic of the proposed filter, a modified $H_{\infty}$ performance index. Analysis results show that the proposed filter has robustness against disturbances, such as process and measurement noises, and against parameter uncertainties. Simulation results show that the proposed filter effectively improves the performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1771-1776
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• 2003

In mobile robot navigation, one of the key problems is the pose estimation of the mobile robot. Although the odometry can be used to describe the motions of the mobile robots quite simple and accurately, the validities of the models are limited by a number of error sources contaminating the encoder outputs so that applying the conventional extended Kalman filter to these nominal model does not yield the satisfactory performance. As a remedy for this problem, we consider the uncertain nonlinear kinematic model of the mobile robot that contains the norm bounded uncertainties and also propose a new robust extended Kalman filter based on the Krein space approach. The proposed robust filter has the same recursive structure as the conventional extended Kalman filter and can hence be readily designed to effectively account for the uncertainties. The computer simulations will be given to verify the robustness against the parameter variation as well as the reliable performance of the proposed robust filter.