Synchronisation of chaotic systems using a novel sampled-data fuzzy controller

Abstract

This paper presents the synchronisation of chaotic systems using a sampled-data fuzzy controller and is meaningful for many physical real-life applications. Firstly, a Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic systems that contain some nonlinear terms, then a type of fuzzy sampled-data controller is proposed and an error system formed by the response and drive chaotic system. Secondly, relaxed LMI-based synchronisation conditions are derived by using a new parameter-dependent Lyapunov-Krasovskii functional and relaxed stabilisation techniques for the underlying error system. The derived LMI-based conditions are used to aid the design of a sampled-data fuzzy controller to achieve the synchronisation of chaotic systems. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.

Structural, optical and magnetic properties of nanocrystalline zinc ferrite particles from glycine assisted combustion: Effect of Sr2+ dopant

“…3a and b. Due to spin orbit coupling, two major Zn 2p 3/2 and Zn 2p 1/2 peaks withbindingenergy ( BE)v alues of 1020.23 eV and 1043.42eVw erei dentified, indicative of the presence of the Zn 2+ ion [29]. After strontium doping ( x =0.05) Zn 2+ ion retains its original oxidation state known from Zn 2p spectra, as showninFig.…”

Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels

“…It is defined as the limiting information rate (in units of information per unit time) that can be achieved with arbitrarily small error probability. [3] Multiple-input multiple-output (MIMO) technology has been used for increasing the channel capacity and information transmission rate, and has been widely investigated in cooperative communication, [4] wireless sensor networks, [5,6] terahertz communication systems, [7] fuzzy systems, [8] etc.…”

Further studies on stability analysis of nonlinear Roesser-type two-dimensional systems

“…On the other hand, the Takagi-Sugeno (TS) fuzzy model has become an efficient tool for dealing with the problem of stability analysis and control synthesis of dynamical nonlinear systems, [9][10][11][12][13][14][15] essentially due to the fact that it could effectively approximate a wide class of nonlinear systems by a 'blending' of several local linear sub-system. The earlier results on stability analysis and control synthesis via the TS fuzzy models are implemented by applying the common Lyapunov function.…”