• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.282-285
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• 1989

This paper presents a new algorithm for position control of the BALL-HOOP system driven by th D.C. servo motor-through the micro computer simulation. The Stale Feed back + PID control algorithm is proposed. This algorithm performs that the settling time is faster and overshoot is decreased more remarkably than the PID and the State Feedback algorithm alone. In this simulation the difference equations are used to calculate the output of the control system.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.287-290
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• 1995

Recently H$_{\infty}$ control theory for nonlinear systems based on the Hamilton-Jacobi inequality has been developed. In this paper, we apply the state feedback controller solved via Riccati equation to a semi-active suspension model, two degree of freedom vehicle model, and show that it is effective for vibration control..

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.23-23
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• 2000

In this paper, we proposed the problems of robust stability and 개bust H$_{\infty}$ control of discrete time-delay linear st.stems with Frobenius norm-bounded uncertainties. The existence condition and the design method of robust H$_{\infty}$ state feedback control]or are given. Through some changes of variables and Schur complement, the obtained sufficient condition can be rewritten as an LMI(linear matrix inequality) form in terms of all variables.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.1-11
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• 1996

In this paper, a robust receding horizon control algorithm, which can be employed for a wide class of nonlinear systems with control and state constraints, modeling errors, and disturbances, is considered. In a neighborhood of the origin, a linear feedback controlelr for the linearized system is applied. Outside this neighborhood, a receding horizon control is applied. Robust stability is proved considering the time taken to solve an optimal control problem so that the proposed algorithm can be applied as an on-line controller.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.280-288
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• 1998

In this paper, a novel relation between the weighting matrix Q in LQR and the eigenstructure of the desired closed-loop system is proposed. Thus, the state feedback gain with the desired eigenstructure in the LQR can be obtained. The proposed scheme is applied to design a simple 3rd-order system and a flight control system design to show the usefulness of the scheme.

• Korean Journal of School Psychology
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• v.16 no.2
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• pp.207-230
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• 2019

This study examined the effect of Attention Feedback Awareness and Control Training(A-FACT) on attention bias and generalized anxiety symptoms in college students. A total of 31 college students with at least 10 points on the Generalized Anxiety Disorder 7-item (GAD-7) scale or at least 56 points on the Korean version of the Penn State Worry Questionnaire (K-PSWQ) with attention bias were randomly assigned to one of three groups: A-FACT( n = 11), Attention Bias Modification (ABM)(n = 10) and Active Placebo Control (APC)(n = 10). Participants in A-FACT group received real-time feedback on attention bias based on their Baseline Neutral Response time(BNR) during A-FACT using a dot probe task. Participants in the ABM group received standard ABM, and those in the APC performed a dot probe task that they were informed was a program to reduce attention bias, but feedback was not provided. A total of eight sessions was conducted twice a week over a 4-week period. After every two sessions, GAD-7, K-PSWQ and K-STAI were rated. The effect of attention bias modification training was rated by changes in the Attention Bias Score(ABS), and in GAD-7, K-PSWQ and K-STAI scores. The results of repeated measure ANOVA indicated that the A-FACT group showed a significant decrease in ABS as well as in GAD-7, K-PSWQ and K-STAI scores compared to the other groups. Current results suggest that self-regulatory control of attention, that is, recognition of bias through feedback in A-FACT, may be effective in alleviating attention bias and generalized anxiety symptoms by recognizing bias through feedback on bias in attention bias modification training.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.95-103
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• 2002

This paper deals with the H$_{\infty}$ control problems for discrete-time linear systems with time-varying delays in states. The existence condition and the design method of the H$_{\infty}$ state feedback controller are given. In this paper, the H$_{\infty}$ control law is assumed to be a memoryless state feedback, and the upper-bound of time-varying delay and S-procedure are used. Through some changes of variables and Schur complement, the obtained sufficient condition can be rewritten as an LMI(linear matrix inequality) form in terms of all variables.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.320-325
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• 1998

Underwater robotic vehicles (URVs) have been an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system becomes one of the most critical subsytems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. In this paper a new type of fuzzy model-based controller based on Takagi-Sugeno-Kang fuzzy model is designed and applied to the control of of an underwater robotic vehicle. The proposed fuzzy controller : 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule ; 2) can guarantee the stability of the closed-loop fuzzy system ; 3) is relatively easy to implement. Its good performance as well as its robustness to the change of parameters have been shown and compared with the re ults of conventional linear controller by simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.689-697
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• 2005

In this paper, an application of a decentralized $H_{\infty}$ controller(DHC) to multiple controlled-permanent magnet(CMAG) magnetic levitation(Maglev) systems is presented. The designed DHC using two Riccati equations iteratively has simpler structure and needs less computational loads than conventional centralized $H_{\infty}$ controller. A target plant is a hybrid-type CMAG system with permanent magnet and coil, and its mathematical model is firstly derived to design the DHC. To implement the designed algorithm, a real Maglev vehicle system including digital controller, chopper, sensor, etc., is manufactured. To compare the performances of the DHC method with an observer-based state feedback control(OSFC), the input tracking and disturbance rejection characteristics are experimentally tested. As performance indices(PI), integral of squared error(ISE), integral of absolute error(IAE), integral of time multiplied by absolute error(ITAE) and integral of time multiplied by squared error(ITSE) are used. From the experimental results, it can be seen that the input tracking and disturbance rejection performances of the DHC are better than those of the conventional controller.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.