Synchronization Control Of Neural Networks Research Articles

Synchronization sampled-data control of uncertain neural networks under an asymmetric Lyapunov–Krasovskii functional method

This paper investigates the synchronization control of neural networks (NNs) considering parameter uncertainties by utilizing an improved asymmetric Lyapunov–Krasovskii functional (ALKF) method. Firstly, an uncertain NNs model with discrete and distributed delays is developed. To synchronize the master–slave system, a memory sampled-data controller is designed. Secondly, an improved ALKF is constructed, in which the positive-definite and symmetric restrictions of matrices are relaxed. Furthermore, improved synchronization criteria are established by linear matrix inequalities (LMIs), which are based on the ALKF method and the integral inequality technique. Finally, two simulation examples are conducted to demonstrate the feasibility and superiority of the established stability conditions in reaching a maximum sampling period.

A novel framework of prescribed time/fixed time/finite time stochastic synchronization control of neural networks and its application in image encryption

In this paper, we investigate a novel framework for achieving prescribed-time (PAT), fixed-time (FXT) and finite-time (FNT) stochastic synchronization control of semi-Markov switching quaternion-valued neural networks (SMS-QVNNs), where the setting time (ST) of PAT/FXT/FNT stochastic synchronization control is effectively preassigned beforehand and estimated. Different from the existing frameworks of PAT/FXT/FNT control and PAT/FXT control (where PAT control is deeply dependent on FXT control, meaning that if the FXT control task is removed, it is impossible to implement the PAT control task), and different from the existing frameworks of PAT control (where a time-varying control gain such as μ(t)=T/(T−t) with t∈[0,T) was employed, leading to an unbounded control gain as t→T− from the initial time to prescribed time T), the investigated framework is only built on a control strategy, which can accomplish its three control tasks (PAT/FXT/FNT control), and the control gains are bounded even though time t tends to the prescribed time T. Four numerical examples and an application of image encryption/decryption are given to illustrate the feasibility of our proposed framework.

A Novel Control Law Design for Prescribed-Time/Fixed-Time Stochastic Synchronization Control of Neural Networks

A Novel Control Law Design for Prescribed-Time/Fixed-Time Stochastic Synchronization Control of Neural Networks

Impulsive Control of Nonlinear Systems With Time-Varying Delay and Applications.

Impulsive control of nonlinear delay systems is studied in this paper, where the time delays addressed may be the constant delay, bounded time-varying delay, or unbounded time-varying delay. Based on the impulsive control theory and some analysis techniques, a new theoretical result for global exponential stability is derived from the impulsive control point of view. The significance of the presented result is that the stability can be achieved via the impulsive control at certain impulse points despite the existence of impulsive perturbations which causes negative effect to the control. That is, the impulsive control provides a super performance to allow the existence of impulsive perturbations. In addition, we apply the theoretical result to the problem of impulsive control of delayed neural networks. Some results for global exponential stability and synchronization control of neural networks with time delays are derived via impulsive control. Three illustrated examples are given to show the effectiveness and distinctiveness of the proposed impulsive control schemes.

Adaptive Semi-Periodically Intermittent and Lag Synchronization Control of Neural Networks With Mixed Delays

In this paper, the lag exponential synchronization for a class of neural networks with distributed delays and discrete delays (mixed delays) is studied via adaptive semiperiodically intermittent control. Using the adaptive control theory, the Lyapunov stability theory combined with the method of intermittent control, the simple but robust adaptive semiperiodically intermittent controller and impulse controller are designed. Via the proposed control methods, the response system can lag synchronize with the drive system, and the less conservative results are obtained. Using the adaptive control approach and giving a rigorous proof for the synchronization scheme, the proposed controllers are obviously little costly and more useful in practice than before. In the original references, the control width should be larger than the time delay and the time delay should be smaller than the noncontrol width. While, in this paper, these strict assumptions can be removed. Moreover, the control time and the control rate may not be constants. This leads to a larger application scope for our method. Last, numerical simulations are exploited to show the effectiveness of the results.