• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.569-572
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• 1996

Explicit state-space formulate for an H$_{.inf}$ based two-degrees-of-freedom robust controller are derived in discrete-time. The controller provides robust stability against coprime factor uncertainty, and a degree of robust performance in the sense of making the closed-loop system match a prespecified reference model. It is shown that the controller consists of a plant observer, the chosen reference model, and a generalized state feedback law associated with the plant and model states. The controller structure is shown to be relatively simple and thus may reduce the computational load on the digital control processor.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.11-19
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• 2013

This paper presents the battle space model, which is capable of propagating various types of emissions from platforms in underwater warfare simulation, predicting interesting encounters between pairs of platforms, and managing environmental information. The battle space model has four components: the logger, spatial encounter predictor (SEP), propagator, and geographic information system (GIS) models. The logger model stores brief data on all the platforms in the simulation, and the GIS model stores and updates environmental factors such as temperature and current speed. The SEP model infers an encounter among the platforms in the simulation, and progresses the simulation to the time when this encounter will happen. The propagator model receives various emissions from platforms and propagates these to other "within-range" platforms by considering the propagation losses and delays. The battle space model is based on the discrete event system specification (DEVS) and the discrete time system specification (DTSS) formalisms. To verify the battle space model, simple underwater warfare between a battleship and a submarine was simulated. The simulation results with the model were the same as the simulation results without the model.

• Kyungpook Mathematical Journal
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• v.47 no.4
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• pp.601-608
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• 2007

In this paper we introduce a discrete model of brucellosis happened in Korean livestock farms and numerically analyze its dynamical features. To do it, we consider parameters data supported by Livestock Cooperatives. To control brucellosis, we investigate the relationship among key parameters, as applications of our model. We hope that our model may be used to reduce brucellosis in Korean livestock farms.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Journal of the Korean Mathematical Society
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• v.48 no.4
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• pp.775-795
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• 2011

The disturbance attenuation problem for a class of discretetime switched linear systems with exponential uncertainties via switched state feedback and switched dynamic output feedback is investigated, respectively. By using Taylor series approximation and convex polytope technique, exponentially uncertain discrete-time switched linear system is transformed into an equivalent switched polytopic model with additive norm bounded uncertainty. For such equivalent switched model, one designs its switching strategy and associated state feedback controllers and dynamic output feedback controllers so that whole switched model is asymptotical stabilization with H-in nity disturbance attenuation base on switched Lyapunov function and LMI approach. Finally, two numerical examples are presented to illustrate our results.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.314-320
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• 2005

In this paper, a methodology for estimating the parameters of a discrete-time system and designing a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems occurring regarding parameter estimation and controller design, a pseudo parallel genetic algorithm (PPGA) is used. The parameters of a discrete-time system are estimated using both the model technique and a PPGA. The digital PID controller is described by the pulse transfer function and its parameters are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.180-185
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• 2008

A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.

• Water for future
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• v.24 no.3
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• pp.61-70
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• 1991

the relationships between rainfall and runoff are analyzed statistically and modelled using discrete linear transfer function, which can be shown with the relations between input and output in hydrologic system. The procedures of identification, estimation and diagnostic checking of model are proposed, and the suitabilith of assume model is determined by the statistics used in time series analysis.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1139-1144
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• 1990

In this paper, we consider linear periodic discrete-time control systems under periodic compensation. Such a closed-loop system generally represents a periodic time-varying system. We examine the problem of finding a compensator such that the closed-loop system is realized as LTI model (if possible) with the closed-loop stability being satisfied. We present a necessary and sufficient condition for solving such problem and also give the characterization of realizable LTI models.