• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.9-19
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• 2013

This paper deals with fuzzy $H_{\infty}$ filtering problem of discrete-time nonlinear Markovian jump systems with state and output time delays. The purpose is to design fuzzy $H_{\infty}$ filter such that the corresponding estimation error system with time delays and initial state uncertainties is stochastically stable and satisfies an $H_{\infty}$ performance level. A sufficient condition for the existence of fuzzy $H_{\infty}$ filter is given in terms of matrix inequalities. In order to relax conservatism, a stochastic mode dependent fuzzy Lyapunov function is employed. The Lyapunov function not only is dependent on the operation modes of system, but also includes the fuzzy membership functions. An illustrative example is finally given to show the applicability and effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.12
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• pp.1302-1307
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• 1991

This paper presents robustness properties of Kalman filters for linear time-invariant systems with delays in both the state and the output. The circle condition concerning the return difference matrix is derived. From the circle condition, it can be seen that the Kalman filter guarantees such nondivergence margins as (1/2,$\infty$) gain margin and $\pm$60$^{\circ}$phase margin, which are the same as those for ordinary systems. The results in this paper might be expected to make theoretical background on extending the LQG/LTR method to systems with delay in the output.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.2
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• pp.174-180
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• 1998

Robust stability of discrete-time regulators which utilize state predictors to compensate computation delays is considered. Novel expressions for the return difference matrices and the complementary sensitivity matrices at the input and the output of the regulator are found to obtain simple bounds for unstructured perturbations. Robust stability for pertubations of the system matrix and /or the gain matrix is also considered. under certain restriction on the nominal system simple bounds for the pertubations are obtained directly from the characteristic equation. It is shown that as far as the effect of the computation delays concerns these bounds have explicit relation to those for the unstructured pertubations.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.2
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• pp.1-6
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• 2012

Control Theory for continuous-time system has been well developed. Due to the development of computer technology, digital control scheme are employed in many areas. When delays are in control systems, it is hard to control the system efficiently. Delays by controller-to-actuator and sensor-to-controller deteriorate control performance and could possibly destabilize the overall system. In this paper, a new approximated discretization method and digital design for control systems with multiple state, input and output delays and a generalized bilinear transformation method with a tunable parameter are also provided, which can re-transform the integer time-delayed discrete-time model to its continuous-time model. Illustrative examples are given to demonstrate the effectiveness of the developed method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.151-156
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• 1998

This paper presents an $H_{\infty)$ output feedback controller design method for linear systems with delayed state, delayed control input, and delayed masurement output. Using a Lyapunov functional, the stability for delayed systems is discussed independently of delays. Also, sufficient condition for the existence of $H_{\infty)$ controllers of any order is given in terms of three linear matrix inequalities(LMIs). Based on positive definite solutions of their LMIs, we briefly explain the way to construct $H_{\infty)$ controller, which stabilizes time-delay systems independently of delays and guarantees an $H_{\infty)$norm bound.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.1-14
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• 2008

This paper presents a convex optimization method for observer-based mixed $H_2/H_{\infty}$ control design of linear systems with time-varying state, input and output delays. Delay-dependent sufficient conditions for the design of a desired observer-based control are given in terms of linear matrix inequalities (LMIs). An observer-based controller which guarantees asymptotic stability and a mixed $H_2/H_{\infty}$ performance for the closed-loop system of the linear system with time-varying delays is then developed. A Lyapunov-Krasovskii method underlies the observer-based mixed $H_2/H_{\infty}$ control design. A numerical example with simulation results illustrates the effectiveness of the methodology.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.271-271
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• 2000

This paper considers guaranteed cost output feedback controller for the uncertain time-varying delay systems with delays in state and control input. The uncertainty in the system is assumed to be norm-bounded and time-varying. The sufficient condition for the existence of controller and the guaranteed cost output feedback controller design method are presented. Also, using some changes of variables and Schur complements, the obtained sufficient condition can be reformulated as LMI forms in terms of transformed variables. Using the obtained LMI variables, we derive guaranteed cost controller gain and guaranteed cost.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.109-114
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• 1997

In this paper, we present an output feedback $H^\infty$controller design method and derive the sufficient condition of the bounded real lemma for linear systems with multiple delays in states. For state delayed systems, sufficient conditions for the existence $\kappa$-th order $H^\infty$controllers are given in terms of three linear matrix inequalities(LMIs). Furthermore, we show how to construct such controllers from the positive definite solutions of their LMIs and given an example to illustrate the validitiy of the proosed design procedure.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.48-51
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• 1996

This note considers the $H^{\infty}$ controller design problem for linear systems with time-varying delays in states. We obtain sufficient conditions for the existence of k-th order $H^{\infty}$ controllers in terms of three linear matrix ineualities(LMIs). These sufficient conditions are dependent on the maximum value of the time derivative of time-varying delay. Furthermore, we briefly explain how to construct such controllers from the positive definite solutions of their LMIs and give an example.e.