• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1488-1497
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• 1989

In this paper, a new adaptive control scheme is proposed that uses a special form of rational function-type linear operator in the parameter adaptation and that removes the augmenting signal terms of the control input components. This adaptation scheme is applied to the MRAC of continuous-time, linear time-invariant, minimum-phase plants whose relative degrees are arbitrary. This scheme can be applied without any change of the controller structure to the adaptive systems regardless of the relative degree if it is greater than 1. And this scheme does not require any signal augmentation for arbitrary relative-degree plants if the reference model has no zeros. The asymptotic stability of the adaptive systems controlled by this scheme is shown by a hyper-stability method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.121-127
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• 2015

This paper considers the problem of sampled-data control for continuous linear parameter varying (LPV) systems. It is assumed that the sampling periods are arbitrarily varying but bounded. Based on the input delay approach, the sampled-data control LPV system is transformed into a continuous time-delay LPV system. Some less conservative stabilization results represented by LMI (Linear Matrix Inequality) are obtained by using the Lyapunov-Krasovskii functional method and the reciprocally combination approach. The proposed method for the designed gain matrix should guarantee asymptotic stability and a specified level of performance on the closed-loop hybrid system. Numerical examples are presented to demonstrate the effectiveness and the improvement of the proposed method.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.361-366
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• 2002

It has been reported that neural network with cyclic connections generates limit cycles. The dynamics of discrete time network with cyclic connections has been analyzed. But the dynamics of cyclic network in continuous time has not been known well due to its huge calculation complexity. In this paper, we study the dynamics of the continuous time network with cyclic connections and the effect of chaotic signal in the network for transitions between limit cycles.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.4
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• pp.22-28
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• 2002

It has been reported that neural network with cyclic connections generates limit cycles. The dynamics of discrete time network with cyclic connections has been analyzed. But the dynamics of cyclic network in continuous time has not been known well due to its huge calculation complexity. In this paper, we study the dynamics of the continuous time network with cyclic connections and the effect of chaotic signal in the network for transitions between limit cycles.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.407-412
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• 1990

This note presents a novel algorithm for a continuous-time direct adaptive pole placement control for single-input single-out nonminimum phase systems. Although the resulting overall closed-loop system is locally stable, assumptions about parameter convergence or the nature of the external input are not considered.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.94.2-94
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• 2002

$\textbullet$ The method to have real-time response at the motion control. $\textbullet$ The trajectory generation method guarantees the continuous acceleration in changing the velocity during the actuator is moving. $\textbullet$ We propose the velocity profile generation algorithm in order to change object position or object velocity with continuous acceleration using blending method.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.396-401
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• 2006

It is well-known that a neural network with cyclic connections generates plural limit cycles, thus, being used as a memory system for storing large number of dynamic information. In this paper, a continuous-time cyclic connection neural network was built so that each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$. The type and the number of limit cycles generated by such network has also been demonstrated through simulation. In particular, the effect of chaos signal for transition between limit cycles has been tested. Furthermore, it is evaluated whether the chaotic noise is more effective than random noise in the process of the dynamical neural networks.

• International Journal of Aerospace System Engineering
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• v.2 no.1
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• pp.43-46
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• 2015

Aeroelastic gust response analysis plays an important role in design of aircrafts. For gust response analysis, frequency domain aerodynamics method has been typically used with generalized aerodynamic influence coefficient matrices at various reduced frequencies. However, it cannot be applied to the aeroservoelastic analysis, such as gust alleviation control. Time-domain state space (SS) models must be built. It attacks little attention that gust response analysis relies on continuous gust time-domain input signal in terms of its PSD function. The aim the current study is to provide a reduced-order modeling (ROM) method based on CFD to model gust responses for continuous gust responses for continuou gust inputs in time domain. The paper analyzed the gust response of AGARD445.6 wing subjected to the Dryden gust with ROMs and compared the difference between the rigid structure and elastic one. The results demonstrate that structure elastic effect effect should be considered in the design of aircraft.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.134-139
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• 2008

Most approaches for continuous review inventory problem need tables for loss function and cumulative standard normal distribution. Furthermore, it is time-consuming to calculate order quantity (Q) and reorder point (r) iteratively until required values are converged. The purpose of this paper is to develop a direct method to get the solution without any tables. We used approximation approaches for loss function and cumulative standard normal distribution. The proposed method can get the solution directly without any iterative procedure for Q, r and without any tables. The performance of the proposed approach is tested by using numerical examples. The budget constraint of this paper assumes that purchasing costs are paid at the time an order is arrived. This constraint can be easily replaced by capacity constraint or budget constraint in which' purchasing costs are paid at the time an order is placed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1593-1598
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• 2004

In this paper, we use the input and output maps and develop simple procedures to obtain realizations for linear continuous-time systems. The procedures developed are numerically efficient and yield explicit formulae for the state space matrices of the realization in terms of the system parameters, notably the system modes. Both cases of the systems with distinct modes and repeated modes are treated. We also present a procedure for converting a realization obtained through the input or output map into the Jordan canonical form. The transformation matrices required to bring the realization into the Jordan canonical form are specified entirely in terms of the system modes.