Variable universe adaptive fuzzy sliding mode projective synchronization of hyperjerk system based on disturbance observer

In this paper, a sliding mode projective synchronization strategy based on disturbance observer and fuzzy system is presented to implement projective synchronization of hyperjerk system with low time-varying disturbance and white noise. Theoretical analysis and numerical calculation show that the disturbance observer can approach the low time-varying disturbance very well. The application of disturbance observer reduces the chattering of the controller. Variable universe adaptive fuzzy control (VUAFC) method is utilized to further reduce the chattering phenomenon. The simulation results demonstrate the effectiveness of the proposed controller.

Quasi-Projective Synchronization of Distributed-Order Recurrent Neural Networks

In this paper, the quasi-projective synchronization of distributed-order recurrent neural networks is investigated. Firstly, based on the definition of the distributed-order derivative and metric space theory, two distributed-order differential inequalities are obtained. Then, by employing the Lyapunov method, Laplace transform, Laplace final value theorem, and some inequality techniques, the quasi-projective synchronization sufficient conditions for distributed-order recurrent neural networks are established in cases of feedback control and hybrid control schemes, respectively. Finally, two numerical examples are given to verify the effectiveness of the theoretical results.

General decay projective synchronization of memristive competitive neural networks via nonlinear controller

In this paper, the general decay projective synchronization of a class of memristive competitive neural networks with time delay is studied. Firstly, a nonlinear feedback controller is designed, which does not require any knowledge about the activation functions. Then, some new and applicable conditions dependent on the Lyapunov function and the inequality techniques are obtained to guarantee the general decay projective synchronization of the considered systems under the developed controller. Unlike other forms of synchronization, projective synchronization can improve communication security due to the scaling constant’s unpredictability. In addition, the polynomial synchronization, asymptotical synchronization, and exponential synchronization can be seen as the special cases of the general decay projective synchronization. Finally, a numerical example is given to demonstrate the effectiveness of the proposed control scheme.

Sliding Mode Matrix-Projective Synchronization for Fractional-Order Neural Networks

This work generalizes the projection scaling factor to a general constant matrix and proposes the matrix-projection synchronization (MPS) for fractional-order neural networks (FNNs) based on sliding mode control firstly. This kind of scaling factor is far more complex than the constant scaling factor, and it is highly variable and difficult to predict in the process of realizing the synchronization for the driving and response systems, which can ensure high security and strong confidentiality. Then, the fractional-order integral sliding surface and sliding mode controller for FNNs are designed. Furthermore, the criterion for realizing MPS is proved, and the reachability and stability of the synchronization error system are analyzed, so that the global MPS is realized for FNNs. Finally, a numerical application is given to demonstrate the feasibility of theory analysis. MPS is more general, so it is reduced to antisynchronization, complete synchronization, projective synchronization (PS), and modified PS when selecting different projective matrices. This work will enrich the synchronization theory of FNNs and provide a feasible method to study the MPS of other fractional-order dynamical models.