• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.265-267
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• 2004

A blind separation problem in a multiple-input-multiple-output (MIMO) linear time-invariant (LTI) system with finite-alphabet inputs is considered. A discrete-time matrix equation model is used to describe the input-output relation of the system in order to make full use of the advantages of modern digital signal processing techniques. At first, ambiguity problem is investigated. Then, based on the results of the investigation, a new identifiability condition is proposed for the case of an input-data set which is widely used in digital communication. A probability bound such that an arbitrary input matrix satisfies the identifiability condition is derived. Finally, Monte-Carlo simulation is performed to demonstrate the validity of our suggestions.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1167-1177
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• 1989

In this paper, a generalized adaptive law is proposed which uses a rational function type operator for parameter adjustment. To satisfy the passivity condition of the adaptation block, we introduce a constant feedback gain into the adaptation block. This adaptation scheme is applied to the model reference adaptive control of a continuous-time, linear time-invariant, minimum-phase system whose relative degree is 1. We prove the asymptotic stability of the output error of this adaptive system by hyperstability method. It is shown that by digital computer simulations this law can give a better output error transient response in some cases than the conventional gradient adaptive law. And the output error responses for the several types of the proposed adaptation law are examined in the presence of a kind of unmodeled dynamics.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.131-131
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• 2000

In this paper, a design method of a fault diagnosis filter for a system with multiplicative faults which cause to change its parameters is developed. Linear time-invariant systems are dealt with in discrete-time domain. The residual which is sensitive to a damage of control surface of an aircraft by parity space approach is defined. Next, the fault is isolated by a new decision logic. Control reconfiguration is achieved by the result of fault diagnosis. Finally, the feasibility of the method is illustrated with a simulation study of a fault diagnosis system for a damaged control surface of an aircraft.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.6-52
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• 2002

The method of identifying the plant models in this paper is the Observer Kalman filter identification (OKID) method. This method of system identification has several pertinent advantages. First, it assumes that the system in question is a discrete linear time-invariant (LTI) state-space system. Second, it requires only input and output data to formulate the model, no a priori knowledge of the system is needed. Third, the OKID method produces a psudo-Kalman state estimator, which is very useful for control applications. Last, the modal balanced realization of the system model means that tuncation errors will be small. Thus, even in the case of model order error the results of that error will...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.624-627
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• 2002

Experimental study showed that the existing mathematical model doesn't fully describe the lateral motion of a moving web fur different operating conditions. So, a physically interpretable model of lateral motion of a moving web in a typical web guidance system, operated at Konkuk Univ., was developed using the system identification technique. A well-known Least Square Method based on ARX model was used for the system identification. Lateral displacement of the web was measured at the exit of each span by infrared sensors. The model obtained from identifying a linear time-invariant system for a typical operating condition yields an improved prediction capability of the lateral dynamics of the moving web compared to other mathematical models proposed in literature.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.480-485
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• 2005

Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.630-635
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• 2018

In this paper, we consider the stability condition for the linear discrete systems with time-varying delay and unstructured uncertainty. The considered system has time invariant system matrices for non-delayed and delayed state variables, but its delay time is time-varying within certain interval and it is subjected to nonlinear unstructured uncertainty which only gives information on uncertainty magnitude. In the many previous literatures, the time-varying delay and unstructured uncertainty can not be dealt in simultaneously but separately. In the paper, new stability conditions are derived for the case to which two factors are subjected together and compared with the existing results considering only one factor. The new stability conditions improving many previous results are proposed as very effective inequality equations without complex numerical algorithms such as LMI(Linear Matrix Inequality) or Lyapunov equation. By numerical examples, it is shown that the proposed conditions are able to include the many existing results and have better performances in the aspects of expandability and effectiveness.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.607-613
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• 2007

Eigenstructure assignment provides the advantage of allowing great flexibility in shaping the closed-loop system responses by allowing specification of closed-loop eigenvalues and corresponding eigenvectors. But, the general eigenstructure assignment methodologies cannot guarantee stability robustness to parameter variations of a system. In this paper, we present a novel method that has the capability of exact assignment of an eigenstructure which can consider the probability of instability for LTI (Linear Time-Invariant) systems. The probability of instability of an LTI system is determined by the probability distributions of the closed-loop eigenvalues. The stability region for the system is made probabilistically based upon the Monte Carlo evaluations. The proposed control design method is applied to design a flight control system with probabilistic parameter variations to confirm the usefulness of the method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.285-290
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• 2007

In this paper, we presents robust digital redesign (DR) method for observer-based linear time-invariant (LTI) system. The term of DR involves converting an analog controller into an equivalent digital one by considering two condition: state-matching and stability. The design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed the uncertain parts of given observer-based system more precisely, When a sampling period is sufficiently small, the conversion of a analog structured uncertain system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).