• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.530-535
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• 2004

This paper deals with the unknown input observer (UIO) design problem for a class of linear time-delay systems. A case in which the observer error can completely be decoupled from an unknown input is treated. Necessary and sufficient conditions for the existences of such observers are present. Based on Lyapunov stability theory, thedesign of the observer with internal delay is formulated in terms of linear matrix inequalities (LMI). The design of the observer without internal delay is turned into a stabilization problem in linear systems. Two design algorithms of UIO are proposed. The effect of the proposed approach is illustrated by two numerical examples.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.171-179
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• 2008

This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

• Transactions of The Korea Fluid Power Systems Society
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• v.5 no.1
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• pp.1-5
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• 2008

Pneumatic driving systems have hard non-linear characteristic and large friction force compared with driving power. Hence, it cannot be robust against parameter uncertainties, modelling error, disturbance and noise. In this study, we apply a mixed $H_2/H_{\infty}$ control to the generalized plant for a pneumatic driving apparatus system including parameter uncertainty and disturbance. In order to design the $H_2/H_{\infty}$ controller, we use the LMI technique. To evaluate control performance and robust stability of the designed controller, we compare it with a conventional controller such as PVA(Position-Velocity-Acceleration state controller) using the simulation results. As a result, it can be known that designed controller shows better robust stability than the conventional controller.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1162-1170
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• 2001

This paper proposes a practical gain-scheduling control law considering robust stability and performance of Linear Parameter Varying(LPV) systems in the presence of nonlinearities and uncertainties. The proposed method introduces LMI-based pole placement synthesis and also associates with a recently developed fuzzy control system based on Takagei-Sugenos fuzzy model. The sufficient conditions for robust controller design of linearized local dynamics and robust stabilization of fuzzy control systems are reduced to a finite set of Linear Matrix inequalities(LMIs) and solved by using co-evolutionary algorithms. The proposed method is applied to the longitudinal acceleration control of high performance aircraft with linear and nonlinear simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.492-495
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• 2005

This paper deals with the problem of estimating the asymptotic stability region(ASR) of uncertain variable structure systems with bounded control. Using linear matrix inequalities(LMIs) we estimate the ASR and we show the exponential stability of the closed-loop control system in the estimated ASR. We show that our estimate is always better than the estimate of [3].

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.97-102
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• 2009

In this paper, the problem of stability analysis for networked control systems with norm-bounded parameter uncertainties is investigated. By construction Lyapunov's functional, a new delay-dependent stability criterion for uncertain networked control system is established in terms of LMIs (linear matrix inequalities) which can be easily by various convex optimization algorithms. One numerical example is included to show the effectiveness of proposed criterion.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.583-596
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• 2010

In this paper, the problem of delay-dependent stability analysis for cellular neural networks systems with time-varying delays was considered. By using a new Lyapunov-Krasovskii function, delay-dependant stability conditions of the delayed cellular neural networks systems are proposed in terms of linear matrix inequalities (LMIs). Examples are provided to demonstrate the reduced conservatism of the proposed stability results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2261-2265
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• 2009

In this paper, the problem of delay-dependent stability of uncertain stochastic systems with time-varying delay is considered. The uncertainties are assumed to be norm-bounded. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system are derived in terms of LMI(linear matrix inequality). Two numerical examples are given to show the effectiveness of proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1744-1746
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• 2004

This paper focuses on the problem of asymptotic stabilization for time-delay systems. To this end, a memoryless state feedback controller is proposed. Then, based on the Lyapunov method, a delay-dependent stabilization criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Certain free weighting matrices are used to express this relationship and linear matrix inequalities (LMIs)-based algorithm to design the controller stabilizing the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.137-140
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• 2001

In this paper, we design 75(Takagi-Sugeno) fuzzy controllers for the systems that can be represented by the 75 fuzzy model. We use inverse optimal approach in which the cost function is determined later than the Lyapunov function and its corresponding control input satisfying the design requirements such as stability and decay rate. The obtained design procedure is in the form of solving LMI(Linear Matrix Inequalities), thus very efficient in practice.