• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2066-2073
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• 2008

In this paper, the problem of global asymptotic stability of uncertain stochastic neural networks with delay is considered. The delay is assumed to be time-varying and belong to a given interval. Based on the Lyapunov stability theory, new delay-dependent stability criteria for the system is derived in terms of LMI(linear matrix inequality). Three numerical examples are given to show the effectiveness of proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2521-2529
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• 2018

This paper deals with a sampled-data tracking control problem for the Takagi-Sugeno fuzzy system with external disturbances. We derive a stability condition guaranteeing both asymptotic stability and H-infinity tracking performance by employing a newly proposed time-dependent line-integral fuzzy Lyapunov-Krasovskii functional. A new integral inequality is also introduced, by which the proposed stability condition is formulated in terms of linear matrix inequalities. Finally, the effectiveness of the proposed method is demonstrated through a simulation example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1080-1084
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• 2014

This paper addresses a design technique for formation tracking controllers of discrete-time Takagi-Sugeno fuzzy multi-agent systems based on consensus. The interconnection topology among the agents is expressed as a digraph. The design condition is represented in terms of linear matrix inequalities. Numerical example demonstrates the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.506-515
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• 2006

This paper studies an intelligent digital control for nonlinear systems with multirate sampling. It is worth noting that the multirate control design is addressed for a given nonlinear system represented by Takagi-Sugeno (T-S) fuzzy models. The main features of the proposed method are that i) it is provided that the sufficient conditions for stabilization of the discrete-time T-S fuzzy system in the sense of Lyapunov stability criterion, which is can be formulated in the linear matrix inequalities (LMIs); and ii) the stability properties of the trivial solution of the digital control system can be deduced from that of the solution of its discretized versions. An example is provided for showing the feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.365-370
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• 2007

This paper studies an automation problem of a heating, a ventilating, and an air conditioning (HVAC) for the development of smart space. The HVAC system is described by the fuzzy system for the stability analysis and the controller design. The linear matrix inequalities (LMIs) conditions are derived for the stabilization problem of the closed-loop system under the analog control. Also, it is required to digitally redesign the pre-designed the analog HVAC control system in order to accomplish the remote control via web. It is shown the this digital redesign problem can be converted to the convex optimization problem with the LMI constraints. An example is provided to show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1142-1146
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• 2014

This paper addresses on a $H_{\infty}$ sampled-data stabilization of a Takagi-Sugeno (T-S) fuzzy system. The sampled-data stabilization problem is formulated as a discrete-time stabilization one via a direct discrete-time design approach. It is shown that the sampled-data fuzzy control system is asymptotically stable whenever its exactly discretized model is asymptotically stable. Based on an exact discrete-time model, sufficient design conditions are derived in the format of linear matrix inequalities (LMIs). An example is provided to illustrate the effectiveness of the proposed methodology.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.615-623
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• 2008

This paper proposes an $H_{\infty}$ controller design method for Takagi-Sugeno (T-S) fuzzy systems using a fuzzy basis-function-dependent Lyapunov function. Sufficient conditions for the guaranteed $H_{\infty}$ performance of the T-S fuzzy control system are given in terms of linear matrix inequalities (LMIs). These LMI conditions are further used for a convex optimization problem in which the $H_{\infty}-norm$ of the closed-loop system is to be minimized. To facilitate the basis-function-dependent Lyapunov function approach and thus improve the closed-loop system performance, additional decision variables are introduced in the optimization problem, which provide an additional degree-of-freedom and thus can enlarge the solution space of the problem. Numerical examples show the effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.184-189
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• 2006

This paper deals with a fractional model reduction for T-S fuzzy systems with time varying delayed states. A contractive coprime factorization of time delayed T-S fuzzy systems is defined and obtained by solving linear matrix inequalities. Using generalized controllability and observability gramians of the 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 performed.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.407-412
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• 2012

In this paper, we discuss an observer-based fault tolerant controller design for the unmanned aerial vehicle (UAV) systems with exogenous disturbance. To derive robust controller design conditions, we use $H_{\infty}$ design technique. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to show the effectiveness of the proposed methodology.