Yongbin Yu

Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays

This paper investigates the global asymptotic stability and stabilization of memristive neural networks (MNNs) with communication delays via event-triggered sampling control. First, based on the novel approach in Lemma 1, the concerned MNNs are converted into traditional neural networks with uncertain parameters. Next, a discrete event-triggered sampling control scheme, which only needs supervision of the system state at discrete instants, is designed for MNNs for the first time. Thanks to this controller, the number of control updates could greatly reduce. Then, by getting utmost out of the usable information on the actual sampling pattern, a newly augmented Lyapunov-Krasovskii functional (LKF) is constructed to formulate stability and stabilization criteria. It should be mentioned that the LKF is positive definite only at endpoints of each subinterval of the holding intervals but not necessarily positive definite inside the holding intervals. Finally, the feasibility and effectiveness of the proposed results are tested by two numerical examples.

Impulsive control for T-S fuzzy model-based chaotic systems

A novel impulsive control scheme for Takagi-Sugeno (T-S) fuzzy model based chaotic systems with adaptive feedback is proposed. Firstly, we utilize a T-S fuzzy model to represent a chaotic system with adaptive feedback. Secondly, using comparison methods, a sufficient criterion for the T-S fuzzy model is derived in terms of linear matrix inequalities (LMIs) and the procedure of controller design is given. Finally, as an illustrative example, its application to stabilize the famous Lorenz system shows the effectiveness of the proposed scheme.

Impulsive control of Lurie systems

In this paper the impulsive control scheme of Lurie systems is represented. Using Lyapunovs direct method and comparison technique, we present novel conditions under which impulsively controlled Lurie systems are asymptotically stable, and give the estimate of the upper bound of impulse interval. In particular, globally exponential stability of impulsive control of Lurie systems is presented. Impulsive controller design with examples is provided to show the feasibility and effectiveness of our method finally.

Impulsive control for T-S fuzzy model based time-delay chaotic systems

Based on Lyapunov stability theory and linear matrix inequality (LMI) technique, this paper proposes a novel impulsive control scheme for time-delay chaotic systems based on their Takagi-Sugeno (T-S) fuzzy model. Some sufficient conditions are given to stabilize the T-S fuzzy model with time delay. The proposed control scheme is successfully applied to stabilize a time-delay Chuapsilas circuit.

Impulsive Synchronization for T-S Fuzzy Model-based Chaotic Systems

In this paper, we present an impulsive synchronization method for chaotic systems based on their Takagi-Sugeno (T-S) fuzzy models, using the comparison methods to determine the stability of error systems between the drive and response systems. Some sufficient conditions are derived to synchronize chaotic systems. A numerical example is given to illustrate the obtained results.

Impulsive control for T-S fuzzy model based chaotic systems with adaptive feedback

A novel impulsive control scheme for Takagi-Sugeno (T-S) fuzzy model based chaotic systems with adaptive feedback is proposed. Firstly, we utilize a T-S fuzzy model to represent a chaotic system with adaptive feedback. Secondly, using comparison methods, a sufficient criterion for the T-S fuzzy model is derived in terms of linear matrix inequalities (LMIs) and the procedure of controller design is given. Finally, as an illustrative example, its application to stabilize the famous Lorenz system shows the effectiveness of the proposed scheme.

Absolute Stabilization for Impulsive Control of Chua's Oscillators

Chuas oscillators are the electronic circuit generator of chaotic signals. In this paper the impulsive control scheme of Chuas Oscillators is represented. Using Lyapunovs direct method, we present conditions under which impulsively controlled Chuas Oscillators is absolutely stable. Finally, we provide the effectively impulsive control procedure.

Dissipativity and passivity analysis for memristor-based neural networks with leakage and two additive time-varying delays

Abstract In this paper, the problems of dissipativity and passivity analysis for memristor-based neural networks (MNNs) with both time-varying leakage delay and two additive time-varying delays are studied. By introducing an improved Lyapunov–Krasovskii functional (LKF) with triple integral terms, and combining the reciprocally convex combination technique, Wirtinger-based integral inequality with free-weighting matrices technique, some less conservative delay-dependent dissipativity and passivity criteria are obtained. The proposed criteria that depend on the upper bounds of the leakage and additive time-varying delays are given in terms of linear matrix inequalities (LMI), which can be solved by MATLAB LMI Control Toolbox. Meanwhile, the criteria for the system with a single time-varying delay are also provided. Finally, some examples are given to illustrate the effectiveness and superiority of the obtained results.

Novel discontinuous control for exponential synchronization of memristive recurrent neural networks with heterogeneous time-varying delays

Abstract This paper investigates the exponential synchronization problem of memristive recurrent neural networks (MRNNs) with heterogeneous time-varying delays (HTVDs). First, a novel discontinuous feedback control is designed, in which a tunable scalar is introduced. The tunable scalar makes the controller more flexible in reducing the upper bound of the control gain. Based on this control scheme, the double integral term can be successfully used to construct the LKF. Second, New method for tackling memristive synaptic weights and new estimation technique are presented. Third, based on the LKF and estimation technique, synchronization criterion is derived. In comparison with existing results, the established criterion is less conservatism thanks to the double integral term of the LKF. Finally, numerical simulations are presented to validate the effectiveness and advantages of the proposed results.

Chaotic modeling of time-delay memristive system

This work considers time delay effect on memristive system. Introduced time delay in the feedback circuit of memristive system, the time-delay memristive system is presented. By the means of dynamics analysis and computer simulation, we derive chaotic model of the delayed memristive system.