• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.20-24
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• 1995

In this paper we analyze the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance bounds are presented by the estimation error convariance and they are here expressed by the upper bounds of the difference of the estimation error covariance between the real and nominal values in case of the system with model uncertainties whose upper bounds are imperfrctly known a priori. The performance bounds of the optimal FIR filter are compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.128-134
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• 2014

A real-time, continuous-scale image interpolation method is proposed based on a bilinear interpolation with directionally adaptive low-pass filtering. The proposed algorithm was optimized for hardware implementation. The ordinary bi-linear interpolation method has blocking artifacts. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. The algorithm can also solve the severe blurring problem by selectively choosing low-pass filter coefficients. Therefore, the proposed interpolation algorithm can realize a high-quality image scaler for a range of imaging systems, such as digital cameras, CCTV and digital flat panel displays.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.967-972
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• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.2
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• pp.16-34
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• 1991

It has been widely accepted that expert systems must reason from multiple sources of information that is to some degree evidential - uncertain, imprecise, and occasionally inaccurate - called evidential information. Evidence theory (Dempster/Shafet theory) provides one of the most general framework for representing evidential information compared to its alternatives such as Bayesian theory or fuzzy set theory. Many expert system applications require evidence to be specified in the continuous domain - such as time, distance, or sensor measurements. However, the existing evidence theory does not provide an effective approach for dealing with evidence about continuous variables. As an extension to Strat's pioneeiring work, this paper provides a new combination rule, a new method for mass function transffrmation, and a new method for rendering joint mass fuctions which are of great utility in evidence theory in the continuous domain.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1140-1142
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• 1996

In this paper, a fixed-horizon $H_{\infty}$ tracking control (HTC) for continuous time-varying systems is proposed in state-feedback case. The solution is obtained via the dynamic game theory. From HTC, an intervalwise receding horizon $H_{\infty}$ tracking control (IHTC) for continuous periodic systems is obtained using the intervalwise strategy. The conditions under which IHTC stabilizes the closed-loop system are proposed. Under proposed stability conditions, it is shown that IHTC guarantees the $H_{\infty}$-norm bound.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.193-200
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• 2010

In this paper, the eigenvalue sensitivity analysis is calculated in the power system which is including both generator controllers such as Exciter, PSS and thyristor controlled FACTS devices in transmission lines such as TCSC. Exciter and PSS are continuously operating controllers but TCSC has a switching device which operates non-continuously. To analyze both continuous and non-continuous operating equipments, the RCF method one of the numerical analysis method in discrete time domain is applied using discrete models of the power system. Also the eigenvalue sensitivity calculation algorithm using state transition equations in discrete time domain is devised and applied to a sampled system. As a result of simulation, the eigenvalue sensitivity coefficients calculated using discrete system models in discrete time domain are changed periodically and showed different values compared to those of continuous system model in time domain by the effect of periodic switching operations of TCSC.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.318-323
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• 2005

In this paper, we propose a systematic method of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear system. A parallel distributed compensation (PDC) technique is then used to design a fuzzy model based controller for both stabilization and tracking. Finally, the designed continuous-time controller is converted to an equivalent discrete-time controller by using an intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy model based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, the single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.219-227
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• 2008

The DEVS (Discrete Event Systems Specification) formalism supports specification of discrete event models in a hierarchical modular manner. MATLAB/Simulink is widely used for modeling, simulating and analyzing continuous and discrete time systems. This paper proposes a realization of the DEVS formalism in MATLAB/ Simulink. The proposed design enables to use a great amount of mathematical packages and functions included in MATLAB /Simulink. The design is also employed as real time simulation and hybrid system simulation which is a mixture of continuous systems and discrete event systems. The paper introduces Simulink-DEVS model, in which a simulation algorithm is embedded. The model consists of a Simulink-atomic model and a Simulink-coupled model. In addition, the time advance algorithm to simulate the model is suggested. The algorithm handles the time synchronization and the accommodation of different concepts specific to continuous and discrete event models. Two experimental results are presented for a pure discrete event model and a hybrid model.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.121-126
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• 2000

In the fast sampling limit the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that covers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control system The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.64-74
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• 2014

We show how a supplier can peg cost measures to the reliability of his time guarantees via the penalty costs considered in the framework. The framework also enables us to study the connections between the logistics network and the market. In this context, we show that even when the market base increases significantly, the supplier can still use the logistics network designed to satisfy lower demand density, with only a marginal reduction in profit. Finally we show how the framework is useful to evaluate and compare various logistics system improvement strategies. The supplier can then easily choose the improvement strategy that increases his profit with the minimal increase in his logistics costs.