• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.351-356
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• 2002

This papaer deals with a model reduction problem for linear systems with time varying parameters. For this problem, a controllability Grammian and an observability Grammian are introduced and computed by solving linear matrix inequalities. Using the controllability/observability Grammian, a balanced state space realization for linear parameter varying systems is obtained. From the balanced state space realization, a reduced model can be obtained by truncating not only states but also time varying parameters and an upper bound of the model reduction error is derived as well.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.9
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• pp.44-48
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• 2010

This paper presents an LMI-based method to design an integral sliding mode controller for an uncertain system with a polytopic model. The uncertain system under consideration may have mismatched parameter uncertainties in the state matrix as well as in the input matrix. Using LMIs we derive an existence condition of a sliding surface. And we give a switching feedback control law.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.195-200
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• 2012

To steer a camera is done based on system parameters of the vision system. However, the system parameters when they are used might be different from those when they were measured. As one method to compensate for this problem, this research proposes a gaze-steering method based on LMI(Linear Matrix Inequality) that is robust to variations in the system parameters of the vision system. Simulation results show that the proposed method produces less gaze-tracking error than a contemporary linear method and more stable gaze-tracking error than a contemporary nonlinear method. Moreover, the proposed method is fast enough for realtime processing.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.129-132
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• 1999

This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.100-104
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• 2003

The SVDD(support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to consider the problem of modifying the SVDD into the direction of utilizing ellipsoids instead of balls in order to enable better classification performance. After a brief review about the original SVDD method, this paper establishes a new method utilizing ellipsoids in feature space, and presents a solution in the form of SDP(semi-definite programming) which is an optimization problem based on linear matrix inequalities.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.1-4
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• 1996

This paper presents a state feedback $H^{\infty}$ controller design method for linear systems with delayed states and inputs. We derive a sufficient condition that the closed-loop system is asymptotically stable for all time-delays and that the $H^{\infty}$-norm of the closed-loop transfer function is less than or equal to some prescribed level $\gamma$. And we propose a sufficient condition for the existence of a state feedback $H^{\infty}$ controller using a form of linear matrix inequality(LMI). Furthermore, we show that the state feedback $H^{\infty}$ controllers can be obtained from solutions satisfying LMI.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.15-18
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• 2007

We consider the problem of designing a static output feedback sliding mode control law for linear dynamical systems with mismatched uncertainties in the state matrix. We assume that an output dependent sliding surface guaranteeing the quadratic stability of the sliding mode dynamics is given, the reachability condition is not required to be satisfied globally, and the output feedback sliding mode control law complises both linear and discontinuous parts. We reduce the problem of designing the linear part of the sliding mode control law to a simple LMI problem which offers design flexibility for combining various useful convex design specifications. Our approach does not require state transformation and it can be applied to mismatched uncertain systems.

• Journal of IKEEE
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• v.18 no.4
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• pp.517-522
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• 2014

This paper investigates the consensus problem for linear multi-agent systems with an arbitrary network delay. The sufficient conditions for a state consensus of linear multi-agent systems are provided by using linear matrix inequalities. Moreover, it is shown that under the proposed protocol, the consensus can be achieved even in the presence of an arbitrarily large network delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.81-87
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• 1993

In this paper robust stability conditions are obtained for linear dynamical systems under structured nonlinear time-varying perturbations, using absolute stability theory and the concept of dissipative systems. The conditions are expressed in terms of solutions to linear matrix inequality(LMI). Based on this result, a synthesis methodology is developed for robust feedback controllers with worst-case H$_{2}$ perforrmance via convex optimization and LMI formulation.