In this paper, the event-triggered asynchronous control problem of nonlinear multi-agent systems is investigated based on T-S fuzzy models. In order to rationally utilize network resources and elaborately avoid unnecessary continuous monitoring, an event-triggered mechanism with a new dynamic threshold parameter and a sampler are considered, respectively. Besides, an asynchronous operation method is adopted to deal with the mismatched premise variables between the fuzzy system and fuzzy controller. Based on the Lyapunov stability theory and appropriate inequality, some sufficient criteria in the form of linear matrix inequalities are obtained to ensure the stability of the closed-loop system. Finally, an illustrative example is provided to demonstrate the effectiveness and superiority of the proposed method.

This brief is concerned with stability analysis for delayed neural networks (DNNs). By establishing polynomials and introducing slack variables reasonably, some improved delay-product type of auxiliary polynomial-based functions (APFs) is developed to exploit additional degrees of freedom and more information on extra states. Then, by constructing Lyapunov-Krasovskii functional using APFs and integrals of quadratic forms with high order scalar functions, a novel stability criterion is derived for DNNs, in which the benefits of the improved inequalities are fully integrated and the information on delay and its derivative is well reflected. By virtue of the advantages of APFs, more desirable performance is achieved through the proposed approach, which is demonstrated by the numerical examples.

This paper is devoted to event-triggered stabilization for a class of interval type-2 (IT2) fuzzy systems with aperiodic sampling. Firstly, the IT2 Takagi-Sugeno fuzzy model and sampled-data controllers are established subject to mismatched membership functions. Secondly, considering non-uniform sampling case, a refined adaptive event-triggered communication scheme (RAETCS) is proposed in a hierarchy form to dynamically adjust the direction and rate of event-triggered threshold parameter by state changing trend and relative state error, respectively. Thus, a complete dual-directional regulating mechanism with sensitivity to state variation is reasonably created to give extra flexibility, which is beneficial for preferable tradeoff between control performance and network resource. Thirdly, taking the practical behaviors on the sampling interval $[i_c, i_{c+1}]$ into account, a novel integral type of time-dependent Lyapunov function is constructed, in which not only the information from $x(i_c)$ to $x(t)$ , but also that from $x(t)$ to $x(i_{c+1})$ are fully exploited. Moreover, by virtue of characteristics for looped function, the positive requirement for individual Lyapunov matrix is further relaxed to facilitate more feasible space. Then, the stability criterion and controller design approach are derived based on the Wirtinger-based integral inequality with slack variables. Finally, the numerical examples are provided to demonstrate the effectiveness and advantages of the proposed methods.

This paper is devoted to the stability and stabilization for Takagi-Sugeno (T-S) fuzzy systems with time-varying delays. Firstly, an improved matrix inequality is presented to bound both strictly and non-strictly proper rational functions, which is more general than the existing versions of reciprocally convex lemmas. Secondly, by suitable operations on parameter-dependent polynomial multiplied by state rate, a couple of novel intermediary polynomial-based functions (IPFs) are developed in delay-product types. Benefitting from slack matrices of IPFs, a certain degree of flexibility is furnished. More importantly than that, by feat of adjustment of variable parameter, the resulting conditions will be further endowed with additive freedom, which relaxes the feasible space in a distinctive manner. Thirdly, by utilizing IPFs along with triple integrals, the stability criteria and controller design approach are derived by some advanced integral inequalities. Resorting to elaborate construction of IPFs, the strengths of bounding techniques are sufficiently exploited, and the information on delay derivative is adequately reflected. Consequently, more desirable performances are achieved, while without excessive computational complexity. Finally, the effectiveness of the proposed methods is verified by numerical examples.

This paper considers the problem of asynchronous fault detection filter (FDF) design for T-S fuzzy singular systems via dynamic event-triggered scheme. A mode-dependent dynamic event-triggered scheme is adopted to alleviate the communication load. Besides, a hidden Markov model is introduced to describe the asynchronous phenomenon between the system and the FDF. Firstly, some sufficient criteria are established to ensure that the residual system is stochastically admissible (SA) with a certain $H_\infty$ performance. Secondly, solvability criteria are presented to codesign the desired FDF gains and the event-triggered matrices. Finally, the correctness of the proposed method is shown by two examples.