• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.16-19
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• 1994

This paper describes a design method of compensators for decentralized control systems. Decentralized control problem is convenient to design multi-variable control systems and formulated as a series of independent designs. The proposed design method is composed of some steps, which is sequentially to close loop of the system diagonalized by regarding interactive subsystem as perturbation for current loop. So, on the basis of H$_{\infty}$ control theory, decentralized controllers are designed considering robust stability for diagonal systems with perturbations. A numerical example shows that the proposed design method is effective for multivariable control systems..

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1320-1323
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• 1996

This paper describes an interpolation method for a parametric surface. A parametric surface is approximated to triangular mesh surfaces and then the basic paths are achieved. As the generated path is a series of linear segments, this algorithm can be easily adapted to general NC controllers. The generated paths have minimal transfer length and are gouge-free within the approximation tolerance. The problems, induced when the paths are represented by linear segments, are overcome without making any path deviation by this algorithm. This algorithm saves machining time by eliminating overdetermined tool paths and keeping the desired average feedrate, which improve productivity and lead to lower production costs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2112-2115
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• 2005

This paper considers the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, through singular value decomposition, some changes of variables, and Schur complements, the sufficient condition can be rewritten as LMI form in terms of transformed variables. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Finally, a numerical example is given to illustrate the design method.

• 제어로봇시스템학회논문지
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• 제20권11호
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• pp.1118-1124
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• 2014

This paper proposes a novel controller design scheme for multimachine power systems based on the explorized policy iteration. Power systems have several uncertainties on system dynamics due to the various effects of interconnections between generators. To solve this problem, the proposed method solves the LQR (Linear Quadratic Regulation) problem of isolated subsystems without the knowledge of a system matrix and the interconnection parameters of multimachine power systems. By selecting the proper performance indices, it guarantees the stability and convergence of the LQ optimal control. To implement the proposed scheme, the least squares based online method is also investigated in terms of PE (Persistency of Excitation), interconnection parameters and exploration signals. Finally, the performance and effectiveness of the proposed algorithm are demonstrated by numerical simulations of three-machine power systems with governor controllers.

• 전자공학회논문지SC
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• 제37권6호
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• pp.7-14
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• 2000

본 논문에서는 부 시스템간의 상호 연결 시 시간지연을 갖는 이산시간영역의 섭동을 갖는 대규모 시스템의 강인 안정화를 위한 분산 제어기를 설계한다. 안정화를 도모하기 위하여 상태 궤환 제어기를 이용하였으며, 이러한 제어기의 존재를 보장하는 충분조건을 리아프노프 안정성 해석법을 이용하여 선형행렬 부등식으로 표현하였다. 이 부등식의 해는 다양한 최적화 알고리즘을 이용하여 쉽게 찾을 수 있으며, 이 부등식의 해로부터 제어기의 게인 행렬도 쉽게 구할 수 있다. 제안된 방법을 예제를 통하여 살펴보았다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.132-135
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• 2000

The development of a robot system being able to work instead of human in the hazardous environment have been conducted for many year. In this study, the new design of controllers for the Master-Slave system is discussed. The Master-Slave system, force, velocity and torque signals are communicated between a master and a slave system. the conventional requires the enhancement of characteristics of tactility for minute force, precision signals and mechanical abrasion of loader. It is possible b controlling the viscosity of ERF(Electro-rheological fluid) since it varies with the electric field. Design of controller as well comparison between numerical simulation and experiments as will be presented. Futhermore, current methodology is also applicable to design of tele-surgery

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.438-441
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• 2004

In this study, we introduce a noble neurogenetic approach to the design of fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and Fuzzy-Set based Neural Networks (FSNN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out by using GAs, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based FSNN. The developed approach is applied to a nonlinear system such as an inverted pendulum where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.416-419
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• 2001

In this paper a new approach to estimate scaling factors of fuzzy controllers such as the fuzzy PID controller and the fuzzy PD controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors[1]. The desist procedure dwells on the use of evolutionary computing(a genetic algorithm) and estimation algorithm for dynamic systems (the inverted pendulum). The tuning of the scaling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as Neuro-Fuzzy model, and regression polynomial [7]. This method can be applied to the nonlinear system as the inverted pendulum. Numerical studies are presented and a detailed comparative analysis is also included.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.27.3-27
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• 2001

In this paper, a robust receding horizon controller for uncertain linear time-varying systems is presented in the dynamic output-feedback form. The existing output-feedback receding horizon controller in the literature is composed of a state observer and a static controller associated with the observer states (similar to LQC control), where the fundamental assumption is that the state observer will supply the exact states as time goes up. The performance of those controllers may be much degraded and even the closed-loop stability may not be guaranteed when the system suffers from disturbances and uncertainties or is time-varying. The proposed controller, which is not necessary to have the state-observer, overcomes such difficulties. Using matrix inequality conditions on the terminal weighting matrix, the closed-loop system stability is guaranteed. Numerical examples are ...