• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.147-150
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• 1997

In the study, we consider chua's circuit which is a paradigmatic chaotic system belonging to Lur'e form. It is shown that the dynamic behavior of such a system can be influenced in such a way as to obtain out of chaotic behavior a desired periodic orbit corresponding to an unstable periodic trajectory which exists in the system. This kind of control can be achieved via injection of a single continuous time signal representing the output of the system associated with an unstable periodic orbit embedded in the chaotic attractor We investigate the case when this signal is sampled, i.e. we supply to the system the control signal at discrete time moments only.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1960-1965
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• 2005

This paper presents theory for stability analysis and design of a servo system for a MIMO Wiener system with nonlinear uncertainty. The Wiener system consists of a linear time-invariant system(LTI) in cascade with a static nonlinear part ${\psi}$(y) at the output. We assume that the uncertain static nonlinear part is sector bounded and decoupled. In this research, we treat the static nonlinear part as multiplicative uncertainty by dividing the nonlinear part ${\psi}$(y) into ${\phi}$(y) := ${\psi}$(y)-y and y, and then we reduce this stabilizing problem to a Lur'e problem. As a result, we show that the servo system with no steady state error for step references can be constructed for the Wiener system.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.356-362
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• 2002

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.261-265
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• 2014

This paper studies the problem of the sampled-data control for Lur'e system with nonlinearities. The nonlinearities are expressed as convex combinations of sector and slope bounds. It is assumed that the sampling periods are arbitrarily varying but bounded. By constructing a new augmented Lyapunov-Krasovskii functional which have an augmented quadratic form with states as well as the nonlinear function, the stabilizing sampled-data controller gains are obtained by solving a set of linear matrix inequalities. The effectiveness of the developed method is demonstrated by numerical simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1843-1850
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• 2015

Controlling nonlinear systems with linear feedback control methods can lead to chaotic behaviors. Order increase in system dynamics due to integral control and control parameter variations in PID controlled nonlinear systems are studied for possible chaos regions in the closed-loop system dynamics. The Lur’e form of the feedback systems are analyzed with Routh’s stability criterion and describing function analysis for chaos prediction. Several novel chaotic systems are generated from second-order nonlinear systems including the simplest continuous-time chaotic system. Analytical and numerical results are provided to verify the existence of the chaotic dynamics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.78-82
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• 2002

In this paper, we have studied a numerical stability analysis method for the robust fuzzy feedback linearization regulator using Takagi-Sugeno fuzzy model. To analyze the robust stability, we assume that uncertainty is included in the model structure with known bounds. For these structured uncertainty, the robust stability of the closed system is analyzed by applying Linear Matrix Inequalities theory following a transformation of the closed loop systems into Lur'e systems.