This article deals with the stability of neural networks (NNs) with time-varying delay. First, a generalized reciprocally convex inequality (RCI) is presented, providing a tight bound for reciprocally convex combinations. This inequality includes some existing ones as special case. Second, in order to cater for the use of the generalized RCI, a novel Lyapunov-Krasovskii functional (LKF) is constructed, which includes a generalized delay-product term. Third, based on the generalized RCI and the novel LKF, several stability criteria for the delayed NNs under study are put forward. Finally, two numerical examples are given to illustrate the effectiveness and advantages of the proposed stability criteria.

This paper concerns the tracking control problem of nonlinear networked control systems (NCSs) considering external disturbance and random package dropouts. The sensor samples system states periodically. The sampled data packages may have dropouts while being transmitted through communication networks. Notice that the number of consecutive lost packages is usually lower and upper bound. Then, an aperiodically sampled data model is employed to describe such a networked control system. By utilizing an augmented state approach, the tracking control problem is transformed into the stabilization for the augmented system. A new two-sided-looped functional (TSLF) is introduced, and the system state and the sampling pattern are fully encountered. Sufficient conditions are derived to design controllers, presented as a series of linear-matrix inequalities (LMIs). A surface-mounted permanent magnet synchronous motor (SMPMSM) model and Rossler's chaotic system are provided to demonstrate the effectiveness of the proposed method.

This article investigates the problem of delay-dependent stability for the one-area load frequency control (LFC) system with electric vehicles (EVs). Two closed-loop models of the LFC system with EVs are proposed, including the model based on the model reconstructed technique and the model with uncertain parameters that considers state of charge. By employing the Lyapunov–Krasovskii functional method, two delay-dependent stability criteria are presented for the systems under study such that a more accurate admissible delay upper bound (ADUB) can be obtained. Case studies are finally carried out to disclose the interrelationship between the ADUB, PI controller gains, and other parameters of the EVs.

This paper deals with the problem of stability and stabilization of Takagi-Sugeno (T-S) fuzzy systems with time-varying delay. First, a novel Lyapunov-Krasovskii functional is constructed, which is dependent on membership-functions and takes more information on the time-varying delay into account. Next, based on an $N$ -order free-matrix-based integral inequality and a switching method, a cluster of criteria on the stability and stabilization are obtained for the closed-loop system connected with switching state-feedback controllers. Then, a parameter tuning method and an iterative algorithm are devised to calculate control gains. Finally, three numerical examples including the truck-trailer system are given to show that the proposed criteria can offer less conservative results than some existing ones.

This article deals with the problem of sampled-data-based synchronization of neural networks with and without considering time delay. A novel looped functional is introduced in the construction of Lyapunov functional, which adequately utilizes the state information of e(tk), e(t), e(tk+1), e(tk-τc), e(t-τc), and e(tk+1-τc). Then, by using this functional and employing a generalized free-matrix-based integral inequality (GFMBII), several sufficient conditions are derived to ensure that the slave system is synchronous with the master system. Also, the sampled-data controller can be obtained by using the linear matrix inequality (LMI) technique. Finally, two numerical examples are illustrated to show the validity and advantages of the proposed method.

This paper deals with the stability of nonlinear multi-agent systems (MASs) with multiple time delays. A class of multi-agent system (MAS) is constructed considering the effects of multiple time delays, nonlinearity, and uncertainty. An integral sliding mode surface is built based on the MAS, and the corresponding sliding mode dynamics are established. Using the Lyapunov method, sufficient conditions are obtained to ensure the sliding mode dynamic asymptotic stability with $H_{\infty }$ performance. Consequently, the sliding mode controller parameter matrix is obtained. Furthermore, a sliding mode control law ensures that the considered system can be driven into the sliding mode surface. Finally, a numerical example is given to demonstrate the usefulness of the theoretical result.