• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.556-561
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• 2002

In this paper, a discrete-time variable structure controller for linear time-varying sampled-data systems with disturbances is proposed. The proposed method guarantees that the system state if globally uniformly ultimately bounded (G.U.U.B), and the ultimate bound is shown to be the order of T, O(T), where T is a sampling period.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.788-792
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• 2010

The problem of delay-dependent and parameter-dependent robust stability condition for discrete-time uncertain singular systems with polytopic uncertainty and interval time-varying delay is considered. A new robust stability condition based on parameter-dependent Lyapunov function is derived in terms of LMI (linear matrix inequality). Moreover, the proposed robust stability condition is a general condition for both singular and non-singular systems. A numerical example is presented to demonstrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.4-33
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• 2001

This paper considers a stochastic discrete algebraic Riccati equation, which is a generalized version of the well-known standard discrete algebraic Riccati equation, and has additional linear terms. Under controllability, observability and the assumption that the additional terms are not too large, the existence of a positive definite solution is guaranteed. It is shown that it arises in optimal control of a linear discrete-time system with multiplicative White noise and quadratic cost. A numerical example is given.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.903-908
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• 2003

In this paper, we present an observer-based robust controller which achieves not only robust stability but also an performance robustness for linear uncertain discrete-time systems. The performance robustness means that comparing the transient behavior of the uncertain system with a desired one generated by the nominal system, the deterioration of control performance (i.e. the error between the real response and the desired one) is suppressed without excessive control input. The control law consists of a state feedback law for the nominal system and a compensation input given by a feedback form of an estimated error signal. In this paper, we show that conditions for the existence of the observer-based controller are given in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to illustrate the proposed technique.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.719-727
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• 2006

This paper proposes a new method to obtain a maximum allowable delay bound for a scheduling of networked discrete control systems and event-based scheduling method. The proposed method is formulated in terms of linear matrix inequalities and can give a much less conservative delay bound than the existing methods. A network scheduling method is presented based on the delay obtained through the proposed method, and it can adjust the sampling period to allocate same utilization to each control loop. The presented method can handle three types of data (sporadic, emergency data, periodic data and non real-time message) and guarantees real-time transmission of periodic and sporadic emergency data using modified EDF scheduling method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.176-176
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• 2000

Generally, discrete-time processing is applied to the uniformly-sampled signals. But, radars emit pulse trains with irregular time instances. In this paper, we formulate the radar pulse train as a stochastic discrete-time dynamic linear model. The estimation task can be done via linear signal processing using Kalman Filter and some considerations. As a result, we can estimate the pulse repetition interval of a pulse train and predict the time instances of the next pulses to be received.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.5
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• pp.1-7
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• 2008

This paper presents not only the robust stabilization technique but also robust non-fragile controller design method for discrete-time singular systems and static state feedback controller with multiplicative uncertainty. The condition for the existence of robust stabilization controller, the admissible controller design method, and the measure of non-fragility in controller are proposed via LMI(linear matrix inequality) approach. In order to get the maximum measure of non-fragility, the obtained sufficient condition can be rewritten as LMI optimization form in terms of transformed variable. Therefore, the presented robust non-fragile controller for discrete-time singular systems guarantees robust stability in spite of parameter uncertainty and controller fragility. Finally, a numerical example is given to show the validity of the design method.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.113-120
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• 1999

One of the important challenges facing control engineers in developing automated machineryis to be able to monitor the machines using remote sensors. Observrs are often used to reconstruct the machine variables of interest. However, conventional observers are unalbe to observe the machine variables when the machine models, upon which the observers are based, have inputs that cannot be measured. Since this is often the case, the authors previsously developed a steady-state optimal state and input observer for time-invariant systems [1], this paper extends that work to time-variant systems. A recursive observer, similar to a Kalman-Bucy filter, is developed . This optimal observer minimizes the trace of the error variance for discrete , linear , time-variant, stochastic systems with unknown inputs.

• Journal of the Korean Mathematical Society
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• v.37 no.4
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• pp.593-611
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• 2000

For linear time-varying control systems with constrained control described by both differential and discrete-time equations in Banach spaces was give necessary and sufficient conditions for exact global null-controllability. We then show that for such systems, complete stabilizability implies exact null-controllability.