• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.8 no.2
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• pp.39-49
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• 2004

Model of the novel Surface motor (SFM) is briefly discussed, and two types of control method including two-order feedback circuit control, indirect acceleration feedback control are analyzed to solve unstable characteristic such as low damp and negative stiffness. The simulation results demonstrate that the system has plain amplitude and wide frequency band arranging from 0 to 8kHz with no resonant peak through indirect acceleration feedback control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1632-1636
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• 2005

This paper presents synchronization of two identical Modified Chua's circuits using two strategies of error feedback coupling. In the first method the synchronization is achieved by linear unidirectional and in the second one by linear bidirectional error feedback coupling. Both proposed methods can make the states of the Modified Chua's circuits globally asymptotically synchronized. Numerical results are provided to show the effectiveness of the proposed approaches and to compare them together based on different criteria.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.496-501
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• 2016

This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.466-471
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• 1994

To make a dynamic system a given desired motion trajectory, a new feedback error learning scheme is proposed which is based on the repeatability of dynamic system motion. This method is composed of feedforward and feedback control laws. A benefit of this control scheme is that the input pattern that generates the desired motion can be formed without estimating the physical parameters of system dynamics. The numerical simulations show the good performance of the proposed scheme

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.373-378
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• 1998

A method to construct a memoryless feedback law for systems with multiple time-delays in the states is proposed. As a plant model, a differential-difference equation with multiple delayed terms is introduced, A stabilizability condition by memoryless feedback is presented. A feedback gain is calculated with a solution of a finite dimensional Riccati equation. It is shown that the resulting closed loop system is asymptotically stable, and moreover, it is a linear quadratic regulator for some cost functional. An alternative stabilizability condition which is easier to check is given.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.349-354
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• 2007

This paper considers the problem of designing static output feedback controllers for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. Based on linear matrix inequality technique, a new method is developed for designing fuzzy stabilizing controllers via static output feedback. Furthermore, the result is also extended to $H_{\infty}$ control. Examples are given to illustrate the effectiveness of the proposed methods.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1137-1139
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• 1996

Feedback Linearization technique needs the exact cancellation of nonlinearity which restricts its application to real environment. To overcome these shortcomings, High-pin feedback is good remedy to this problem. In this paper, we briefly survey the high-gain feedback control technique and show some conditions for applying this method to nonlinear systems. In order to use this technique in real situation, some properties of ${\varepsilon}$-bound and semi-global stabilization are discussed.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.139-148
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• 2010

This paper shows a reinforcement post-processing method and feedback algorithm for improvement of assigning method in classification. Especially, we focused on complex documents that are generally considered to be hard to classify. A basis factors in traditional classification system are training methodology, classification models and features of documents. The classification problem of the documents containing shared features and multiple meanings, should be deeply mined or analyzed than general formatted data. To address the problems of these document, we proposed a method to expand classification scheme using decision boundary detected automatically in our previous studies. The assigning method that a document simply decides to the top ranked category, is a main factor that we focus on. In this paper, we propose a post-processing method and feedback algorithm to analyze the relevance of ranked list. In experiments, we applied our post-processing method and one time feedback algorithm to complex documents. The experimental results show that our system does not need to change the classification algorithm itself to improve the accuracy and flexibility.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1306-1313
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• 2005

Relevance Feedback(RF), a method to use perceptual feedback in image retrieval, refines a query by the relevance information from a user. However, the user's feedback information is thrown away as soon as a search session ends. So, this paper proposes an enhanced version of RF, which is designed to accumulate human perceptual responses over time through relevance feedback and to dynamically combine the accumulated high-level relevance information with low-level features to further improve the retrieval effectiveness. Experimental results are presented to prove the potential of the proposed RF.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.1
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• pp.27-33
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• 2009

Human postural responses appeared to have stereotyped modality, such as ankle mode, knee mode and hip mode in response to various perturbations. We examined whether human postural control gain of full-state feedback could be decoupled along with the eigenvector. To verify the model, postural responses subjected to fast backward perturbation were used. Upright posture was modeled as 3-segment inverted pendulum incorporated with feedback control, and joint torques were calculated using inverse dynamics. Postural modalities such as ankle, knee and hip mode were obtained from eigenvectors of biomechanical model. As oppose to the full-state feedback control, independent eigenvector control assumes that modal control input is determined by the linear combination of corresponding modality. We used optimization method to obtain and compare the feedback gains for both independent eigenvector control and full-state feedback control. As a result, we found that simulation result of eigenvector feedback was not competitive in comparison with that of full-state feedback control. This implies that the CNS would make use of full-state body information to generate compensative joint torques.