• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.2-133
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• 2001

This paper focuses on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several independent, but interacting processes running on two separate stations. By using this NCS, the network delay is analyzed to find the cause of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controllers performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice for NCS due to its robustness against parameter uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.6-129
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• 2001

In this paper, we consider a class of time-varying systems with time-varying state delay. Generally, this system is affected by many uncertainties and we assume that the information of the upper bound(time-delay, uncertainty) is known. In this work, we propose a robust control for system with state delay. The stability based on Lyapunov function is presented. Finally, a numberical example is given to demonstrate the validity of the result.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.125.3-125
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• 2001

Recently, aircraft is designed to have high maneuverable at high angle of attack. However, it is very hard to obtain the accurate dynamic model for the high performance, because aerodynamic characteristics are nonlinear and include a lot of uncertainties. Therefore, nonlinear controller without considering uncertainties may degrade the control system performance. On this paper, to overcome these defects, the neural networks based adaptive nonlinear controller is proposed making use of the backstepping technique. Neural networks are implemented to guarantee robustness to uncertainties caused by aerodynamic coefficients variation. The main feature of the proposed controller is that the adaptive controller is developed under the assumption ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.44.3-44
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• 2002

Stability robustness of a linear time-varying system with time-varying structured state space uncertainties is considered by using extended-mean theorem and Bellman's lemma. The extended-mean theorem is a necessary and sufficient exponential stability criterion based on the recently developed PD-eigenvalue and PD-eigenvector for a linear time-varying system. Our new result required that the extended-mean of each nominal PD-eigenvalue should be negative real which is determined by a norm involving the structures of the uncertainty and the no...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.52-54
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• 1991

In this paper, the robust stability, and the quadratic performance of linear uncertain systems are studied. A quadratic Lyapunov function candidate with time-varying matrix is derived to provide robust stability bounds. Also upper bounds of a quadratic performance is given under the assumption that the uncertain system is stable. Both the robust stability bounds and the upper bounds of a quadratic performance are obtained as solutions of a class of modified Lyapunov equations.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1068-1072
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• 1991

This paper presents a decentralized model reference adaptive control scheme for an interconnected continuous linear system composed of a number of single-input single-output subsystems in which outgoing interactions pass through the measurement channel and are subject to bounded external disturbance. The scheme can treat the unknown strength of interactions as well as the uncertainty of subsystems.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.554-559
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• 1986

This paper considers the problem of stabilizing a composite system formed by interconnecting a number of single-input single-output linear continuous systems. The problem is general in the sense that in addition to the standard assumption about the uncertainty of the subsystems, the strength of interconnections is assumed unknown. A method to design a local adaptive feedback control is first presented, and then the resultant closed-loop system is assured to be globally stable. Also, a numerical example is illustrated via computer simulation.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.809-812
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• 1999

The pendulum is a SIMO(Single-input multi-output) system that both angle of pendulum and position of cart controlled simultaneously by one actuator. In this paper, propose a hybrid neuro-controller to apply to pendulum system. We design the conventional optimal controller and the neural network as a identifier, which can identify the uncertainty of plant not modeled, respectively. Then we combine them into a novel controller, with a structure that the error between plant and identifier is added in conventional optimal control input Finally, the paper shows the validity of the proposed controller through computer simulations and experiments.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.92-101
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• 2006

In this paper a adaptive backstepping control scheme is proposed for control of a do motor driving a one-link manipulator. Fuzzy logic systems are used to approximate the unknown nonlinear function including the parametric uncertainty and disturbance throughout the entire electromechanical system. A compensation controller is also proposed to estimate the bound of approximation error. Thus the asymptotic stability of the closed-loop control system can be obtained. Numerical simulations are included to show the effectiveness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.463-468
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• 1990

A VSC law is derived for the attitude control of an orbiting spacecraft in the presence of disturbance and parameters variation using reaction jets. The switching surface was chosen to be a linear function of tracking error, its derivative and integral. Simulation results are presented to show that in the closed-loop system, precise attitude control is accomplished in spite of uncertainty in the system.