This paper considered generalizedfunctionprojective Synchronisation (GFPS) between identical hyperchaotic systems by utilizing two different matrices with the new class of scaling functions. The nonlinear control ap...
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This paper considered generalizedfunctionprojective Synchronisation (GFPS) between identical hyperchaotic systems by utilizing two different matrices with the new class of scaling functions. The nonlinear control approach is applied for chaos synchronization. The stability analysis of the synchronization error is carried out through Lyapunov's second method. Two different controllers are introduced and a comparison between the two methods is given. Finally, the results were discussed and the effectiveness of this was achieved through numerical theory and simulation.
In the conventional adaptive fuzzy control design, T-S fuzzy systems with linear rule consequents, called typical T-S fuzzy systems, are usually introduced to model controlled systems and approximate nonlinear functio...
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In the conventional adaptive fuzzy control design, T-S fuzzy systems with linear rule consequents, called typical T-S fuzzy systems, are usually introduced to model controlled systems and approximate nonlinear functions. The main advantage of typical T-S fuzzy system is that it makes itself naturally to utilize Lyapunov stability theory. However, typical T-S fuzzy system has finite capability in modeling nonlinear system. This paper investigates the universal approximation of T-S fuzzy systems with random rule consequents, named generalized T-S fuzzy systems. The premise variable of generalized T-S fuzzy system is associated with the system state, which may not be the system state. Moreover, generalized function projective synchronization of different uncertain incommensurate fractional-order chaotic systems with external disturbances and inputs saturation is presented via generalized T-S fuzzy systems. An adaptive controller together with fractional-order parameter adaptation laws is designed based on combining the parallel distributed compensation technique and the fractional Lyapunov stability theory to guarantee the Mittag-Leffler stability in the closed-loop system. The distinctive features of this synchronization control include: (1) the control gain matrix is presumed to be invertible (symmetric or non-symmetric);(2) generalized function projective synchronization design for different fractional-order systems with inputs saturation can be accomplished. Finally, an illustrative example is given to verify the effectiveness of the proposed method.
New sufficient conditions are derived to guarantee the generalized function projective synchronization of weighted cellular neural networks with multiple time-varying delays. Based on Lyapunov theory, this paper gives...
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ISBN:
(纸本)9781479927616
New sufficient conditions are derived to guarantee the generalized function projective synchronization of weighted cellular neural networks with multiple time-varying delays. Based on Lyapunov theory, this paper gives an adaptive feedback controlling method to identify the generalized function projective synchronization of weighted cellular neural networks with time-varying delays. Then, the synchronization of the weighted cellular neural networks with different nodes is considered. The parameters of this paper are considered in many aspects, which can be applied to practical.
generalized function projective synchronization of coupled chaotic systems with parameter mismatch, time-delay and stochastic perturbation is investigated. The synchronization is realized by analyzing the stochastic s...
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generalized function projective synchronization of coupled chaotic systems with parameter mismatch, time-delay and stochastic perturbation is investigated. The synchronization is realized by analyzing the stochastic stability of the error system. According to the invariance principle of the stochastic differential equation, the unknown parameters update laws and the control laws are proposed. The generalized function projective synchronization of coupled chaotic or hyper-chaotic systems is realized. At last, a numerical example is presented to show the effectiveness of the theoretical results.
Combining adaptive control theory with an antisymmetric structure, an extended adaptive controller which is more generalized and simpler than some existing controllers is designed. Under the controller, generalized fu...
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Combining adaptive control theory with an antisymmetric structure, an extended adaptive controller which is more generalized and simpler than some existing controllers is designed. Under the controller, generalized function projective synchronization of two different uncertain hyperchaotic systems is achieved, and the unknown parameters are also estimated. In numerical simulations, the scaling function factors discussed in this paper are more complicated, and they have not been discussed in other papers. Corresponding simulation results are presented to show that the controller works well. (C) 2011 Elsevier Ltd. All rights reserved.
By using the generalized function projective synchronization (GFPS) method, in this paper, a new scheme for secure information transmission is proposed. The Liu system is employed to encrypt the information signal. In...
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By using the generalized function projective synchronization (GFPS) method, in this paper, a new scheme for secure information transmission is proposed. The Liu system is employed to encrypt the information signal. In the transmitter, the original information signal is modulated into the system parameter of the chaotic systems. In the receiver, we assume that the parameter of receiver system is uncertain. Based on the Lyapunov stability theory, the controllers and corresponding parameter update rule are constructed to achieve GFPS between the transmitter and receiver system with uncertain parameters, and identify unknown parameters. The original information signal can be recovered successfully through some simple operations by the estimated parameter. Furthermore, by means of the proposed method, the original information signal can be extracted accurately in the presence of additional noise in communication channel. Numerical results have verified the effectiveness and feasibility of presented method. Mathematics subject classification (2010) 68M10, 34C28, 93A30, 93C40
This research is concerned with the problem of generalized function projective synchronization of nonlinear uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. The considere...
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This research is concerned with the problem of generalized function projective synchronization of nonlinear uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. The considered problem is challenging owing to the presence of unmeasured master-slave system states, external dynamical disturbances, unknown nonlinear system functions, unknown time-varying delays, quantized outputs, unknown control directions unknown actuator nonlinearities (backlash-like hysteresis, dead-zone and asymmetric saturation actuators) and distinct fractional-orders. Under some mild assumptions and using Caputo's definitions for fractional-order integrals and derivatives, the design procedure of the proposed neural adaptive controller consists of a number of steps to solve the generalised functionprojectivesynchronization problem. First, sinooth functions and the mean value theorem are utilized to overcome the difficulties from actuator nonlinearities and distributed time-varying delays, respectively. Then, a simple linear observer is established to estimate the unknown synchronization error variables. In addition, a Nussbaum function is incorporated to cope with the unknown control direction and a neural network is adopted to tackle the unknown nonlinear functions. The combination of the frequency distributed model, the Razumikhin Lemma, the neural network parameterization, the Lyapunov method and the Barbalat's lemma is employed to perform the stability proof of the closed-loop system and to derive the adoption laws. The major advantages of this research are that: (1) the Strictly Positive Real (SPR) condition on the estimation error dynamics is not required, (2) the considered class of master-slave systems is relatively large, (3) all signals in the resulting closed-loop systems are semi-globally uniformly ultimately bounded and the synchronization errors semi-globally converge to zero. Finally, numerical examples are presented to illustrate the p
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