• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.647-655
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• 1999

For linear time-varying systems described by the triple (A(t),B(t),C(t)) where A(t),B(t),C(t) are the system, the input, and the output matrices, respectively, we propose concepts for measures of modal and gross controllability /observability. We introduce a differential algebraic eigenbvalue theory for linear time-varying systems to calculate the PD-eigenvalues and left and right PD-eigenvectors of the system matrix A(t) which will be used to derive the concepts for the measures. The time-dependent angle between the left PD-eigenvectors of the system matrix A(t) and the columns of the input matrix B(t), and the magnitude of the each element of the input matrix B(t) are used to propose the modal controllability measure. Similarly, the time-dependent angle between the right PD-eigenvectors of the system matrix A(t) and the rows of the output matrix C(t) are used to propose the madal observability measure. Gross measure of controllability of a mode from all inputs and its gross measure of observability in all outputs for the linear time-varying systems are also proposed. Numerical examples are presented to illustrate the proposed concepts.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.17-23
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• 2009

In many cases, clustering algorithms have been used for extracting and discovering useful information from non-linear data. They have made a great effect on performances of the systems dealing with non-linear data. Thus, this paper presents a new approach called hierarchically structured clustering algorithm, and it is applied to the prediction system for non-linear time series data. The proposed hierarchically structured clustering algorithm (called HCKA: Hierarchical Cross-correlation and K-means clustering Algorithms) in which the cross-correlation and k-means clustering algorithm are combined can accept the correlationship of non-linear time series as well as statistical characteristics. First, the optimal differences of data are generated, which can suitably reveal the characteristics of non-linear time series. Second, the generated differences are classified into the upper clusters for their predictors by the cross-correlation clustering algorithm, and then each classified differences are classified again into the lower fuzzy sets by the k-means clustering algorithm. As a result, the proposed method can give an efficient classification and improve the performance. Finally, we demonstrates the effectiveness of the proposed HCKA via typical time series examples.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.108-111
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• 1999

In this paper, we develope a composite control law for linear systems with norm-bounded time-varying parameter uncertainties, which consists of a basic linear robust control do-signed so as to generate a desired transient time-response for the worst-case parameter variation and a nonlinear modification term designed so as to reduce cautiousness of the linear robust control in an adaptive manner. The proposed controller is established such that the reduction of cautiousness of the linear robust control is well incorporated into the achievement of a good transient behavior.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.125.1-125
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• 2001

This paper deals with the eigenvalue assignment technique for linear time-varying systems to achieve feedback stabilization. For this, we introduce the novel eigenvalue concepts. Then, we propose the Ackerman-like formula for linear time-varying systems. It is believed that this technique is the generalized version of the Ackerman formula forlinear time-invariant systems. The advantages of the proposed technique are that it does not require the transformation of the original system into the phase-variable form nor the computation of eigenvalues of the original system.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.44.3-44
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• 2002

Stability robustness of a linear time-varying system with time-varying structured state space uncertainties is considered by using extended-mean theorem and Bellman's lemma. The extended-mean theorem is a necessary and sufficient exponential stability criterion based on the recently developed PD-eigenvalue and PD-eigenvector for a linear time-varying system. Our new result required that the extended-mean of each nominal PD-eigenvalue should be negative real which is determined by a norm involving the structures of the uncertainty and the no...

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.210-213
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• 1988

By using Lyapunov method, sufficient conditions for linear time-varying continuous-time and discrete-time systems to be stable are presented under the assumption that the systems are slowly time-varying. Though it is not simple to find the stability regions immediately, one could find practical and large stability regions by constructing an appropriate algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.13-18
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• 2005

This paper considers a design problem of the repetitive control system for linear systems with time-varying norm bounded uncertainties. Using the Lyapunov functional for time-delay systems, a sufficient condition ensuring robust stability of the repetitive control system is derived in terms of an algebraic Riccati inequality (ARI) or a linear matrix inequality (LMI). Based on the derived condition, we show that the repetitive controller design problem can be reformulated as an optimization problem with an LMI constraint on the free parameter.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.521-528
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• 1999

The nth-order, scalar, linear time-varying (LTV) systems can be dealt with operators on a differential ring. Using this differential algebraic structure and a classical result on differential operator factorizaitons developed by Floquet, a novel eigenstructure(eigenvalues, eigenvectors) concepts for linear time0varying systems are proposed. In this paper, Necessary and sufficient conditions for the existence of well-defined(free of finite-time singularities) SD- and PD- spectra for SPDOs with complex- and real-valued coefficients are also presented. Three numerical examples are presented to illustrate the proposed concepts.