• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.571-574
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• 2005

This paper gives some sufficient conditions for a given polyhedral set which is represented as a set of linear inequalities to be positive D-invariant for uncertain linear discrete-time systems in the case such that the systems matrices depend linearly on uncertain parameters whose ranges are given intervals. Further, the results will be applied to uncertain linear continuous systems in the sense of the above by using Euler approximation.

• 전기의세계
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• v.23 no.1
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• pp.69-72
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• 1974

This paper deals with an analytical design of a feedback regulator with vector input is discrete linear time-invariant systems. We have derived some relations such that the eigenvalues of a system plant with vector input under the time-optimal control strategy can be arbitrarily changed by the characteristics of the minor loop compensator which is indroduced in the feedback path.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.565-568
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• 1996

In this paper, a solution method is proposed to calculate the optimum solution to discrete optimal H$_{.inf}$ control problem for feedback of linear time-invariant system states and disturbance variable. From the results of this study, condition of existence and uniqueness of its solution is that transfer matrix of controlled variable to input variable is left invertible and has no invariant zeros on the unit circle of the z-domain as well as extra geometric conditions given in this paper. Through a numerical example, the noniterative solution method proposed in this paper is illustrated.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.680-684
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• 2005

This paper presents a data-based stability analysis of a MIMO linear time-invariant discrete-time system, as an extension of the previous results for a SISO system. In the MIMO case, a similar discussion as in the case of a SISO system is also applied, except that an augmented input and output space is considered whose dimension is determined in relation to both the orders of the input and output vectors and the numbers of inputs and outputs. As certain subspaces of the input and output space, both output data space and closed-loop data space are defined, which contain all the behaviors of a system, respectively, with zero input in open-loop and with a control input in closed-loop. Then, we can derive the data-based stability conditions, in which the open-loop stability can be checked by using a data matrix whose column vectors span the output data space and the closed-loop stability can also be checked by using a data matrix whose column vectors span the closed-loop data space.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.215-226
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• 2005

Loop invariant code motion (LICM) optimization includes relatively heavy code analyses, thus being not readily applicable to Java Just-In-Time (JIT) compilation where the JIT compilation time is part of the whole running time. 'Classical' LICM optimization first analyzes the code and constructs both the def-use chains and the use-def chains. which are then used for performing code motions. This paper proposes a light-weight LICM algorithm, which requires only the def-use chains of loop invariant code (without use-def chains) by exploiting the fact that the Java virtual machine is based on a stack machine, hence generating code with simpler patterns. We also propose two techniques that allow more code motions than classical LICM techniques. First, unlike previous JIT techniques that uses LICM only in single-path loops for simplicity, we apply LICM to multi-path loops (natural loops) safely for partially redundant code. Secondly, we move loop-invariant, partially-redundant null pointer check code via predication support in Itanium. The proposed techniques were implemented in a JIT compiler for Itanium processor on ORP (Open Runtime Platform) Java virtual machine of Intel. On SPECjvrn98 benchmarks, the proposed technique increases the JIT compilation overhead by the geometric mean of 1.3％, yet it improves the total running time by the geometric mean of 2.2％.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.897-899
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• 2004

There is scientific work containing the recurrence method of synthesis the new class of orthogonal circle m-invariant signals: designed effective algorithms of fast-direct computing m-convolution in time domain: engineer methods of design economic scheme of decoders for optimal receiving in aggregate of suggested signal.

• Communications of the Korean Mathematical Society
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• v.10 no.2
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• pp.385-392
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• 1995

Along with certain properties of a chronal or a causal isomorphism, we discuss the invariant nature of a causality conditions of a given space-time.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.158-162
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• 1998

We study the decentralized stabilization problem of linear time-invariant large-scale interconnected systems with delays without any system structure. We obtain sufficient stability conditions for interconnected systems which are equivalent to disturbance attenuation of some scaled system. A decentralized output-feedback controller is obtained using standard H$\infty$ control theory. The obtained controller is delay-independent. We also obtain an observer for the interconnected system.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.818-822
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• 2009

In this paper, we consider a decentralized observer design problem for fault detection in large-scaled linear time-invariant systems. Since the fault detection residual is desired to be sensitive on the fault, we use the H_ index performance criterion. Sufficient conditions for the existence of such an observer is presented in terms of linear matrix inequalities. Simulation results show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.339-344
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• 2000

This paper is concerned with the simplification of complex linear time-invariant systems. A simple technique is suggested using the well-known least squares method in the frequency domain. Given a high-order transfer function in the s- or z-domain, the squared-gain function corresponding to a low-order model is computed by the least squares method. Then, the low-order transfer function is obtained through the factorization. Three examples are given to illustrate the efficiency of the proposed method.