• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.337-342
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• 2009

This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.117-121
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• 1990

The control process involving pure time delays presents a continuing challenge to the control system engineer. The nonlinear nature of the delay which can be introduced into the system make the use of conventional control algorithms a poor prospect. The Smith Predictor was developed to alleviate this problem. Unfortunately the quality of control achieved with the Smith Predictor is known to be sensitive to modelling errors. Only recently have researchers attempted to quantify the Smith Predictor controller's robustness to modelling errors. In several studies stability boundaries were plotted as functions of errors in parameters. But the research results address the question of performance of Smith Predictor controllers, In this paper, the Rule based Expert Systems for performance improvement of the Smith Predictor controller are developed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.299-303
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• 1995

This paper charcterizes dynamics of cold tandem minns, and constructs it state-space model of which are linear time invariant, using subspace method. Step responses particularly show the influence on mass transfer delay. Input-output data set are obtained form nonlinear differential equations including mass transfer delay and nonlinearity. It is shown that the identified state-apace model well approximates the original systems dynamics.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.652-657
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• 1992

This paper presents to accomplish successfully a multi-input real time control by applying control hierarchy for sliding mode of multi-joint manipulators whose nonlinear terms are regarded as disturbances. We- could simplify the dynamic equations of a manipulator and servo system, which are composed of linear elements and nonlinear elements, by assuming that nonlinear terms, which are Inertia term, gravity force term, Coriolis force term and centrifugal force term, are external disturbance. By simplifying that equation, we could easily obtain a control input which satisfy sliding mode of multi-input system. We proposed a new control input algorithm in order to decrease chattering by changing control input according as effect of disturbance if a control response become within allowance error range. In this experiments, we used DSP(Digital Signal Processor) controller to suppress chattering by time delay of calculation and to carry out real time control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.392-395
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• 2008

본 논문은 퍼지 제어기를 이용하여 이산 비선형 뉴트럴 시스템을 안정화 시킨다. 시간 지연을 가지는 이산 비선형 모델에 퍼지 제어기를 연결하여 폐회로를 구성하고, 이에 대한 안정도 분석 및 성능 평가에 대해 연구한다. 이산 비선형 시스템을 먼저 T-S 퍼지모델로 모델링 하고, 모델링된 시스템을 안정화 시키기 위한 제어기를 설계한다. 퍼지 모델과 퍼지 제어기 모두 같은 멤버쉽 함수를 가진다고 가정하며, 제어기 이득값 설계를 위한 선형 행렬 부등식 조건을 유도한다. 모의 실험을 통하여 제안된 제어기의 안정도를 입증한다.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1643-1651
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• 2002

Magnetic levitation systems are required to have a large operating range in many applications. As one method to solve this problem, Time Delay Control (TDC) is applied to a single-axis magnetic levitation system in this paper A reduced-order observer is utilized to estimate states excluding measurable states in the control law. The system consists of a square air-core solenoid and a circular permanent magnet attached on a plastic ball. Theoretical magnetic forces of the system are obtained on the basis of the location of the magnet around the solenoid. The magnetic levitation force is obtained by the experiment, and then compared with the theoretical one. As the results of the control experiments, the nonlinear controller (TDC : 1-2 ㎜) has a larger operating range than the linear controller (PD control : 1-1.4 ㎜), and is superior to linear. control in the robustness to the modeling uncertainty and the performance of the disturbance rejection.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.763-766
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• 1996

A model helicopter is an unstable, multi-input multi-output nonlinear system exposed to strong disturbances and its system parameters change continually. In this paper, Time Delay Control(TDC) is adopted for these reasons. TDC uses past observation of the system's response and the control input to directly modify the control action rather than adjusting the controller gains leading to a model independent robust controller. TDC can force the plant to follow an appropriate reference model, but the reference model cannot be chosen arbitrarily. In this paper the procedure of choosing a reference model and the performance of the controller are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1456-1459
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• 1997

In this paper, a control system using robust H.inf. controller based on convex parametrization is presented for nonlinear system with uncertainty. accounting for the time delay, noise and linearization error by frequency analysis, the suboptmal controller is designed to meet robust stability and performance for uncertainty. The desinged control system is applied to a nonlimear boiler moderl to test its performances.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.214-217
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• 1999

In this paper, genetic algorithm (GA) is implemented to search for the optimal structures (i.e. the kind of neural networks, the number of inputs and hidden neurons) of neural networks which are used approximating a given nonlinear function. Two kinds of neural networks, i.e. the multilayer feedforward [1] and time delay neural networks (TDNN) [2] are involved in this paper. The synapse weights of each neural network in each generation are obtained by associated training algorithms. The simulation results of nonlinear function approximation are given out and some improvements in the future are outlined.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.174-180
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• 2012

This paper proposes a decentralized adaptive output-feedback controller design for nonlinear interconnected systems with unknown time delays. The interaction terms with unknown delays are related to all states of subsystems. The time-delayed functions are compensated by using appropriate Lyapunov-Krasovskii functionals and function approximation technique. The observer dynamic surface design technique is employed to design the proposed memoryless local controller for each subsystem. In addition, we prove that all signals in the closed-loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin.