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 work is concerned with the reliable extended passive control problem for semi-Markov jump Takagi-Sugeno fuzzy systems based on an event-triggered mechanism. An asynchronous approach is utilized to cope with the fuzzy-basis-dependent membership functions in networked fuzzy systems. For fear of the waste of communication resources, an event-triggered mechanism to screen the transmitted data is adopted for Takagi-Sugeno fuzzy semi-Markov jump systems under consideration. Owing to the use of Lyapunov stability theory and some novel integral inequalities based on auxiliary functions, some sufficient conditions are obtained to guarantee that the resulting closed-loop system not only meets a prescribed mixed $\mathcal{H}_{\infty }$ and passive performance but also is stochastically stable. Then, by using a skillful matrix decoupling approach, the gains of the fuzzy controller may be expressed specifically. Lastly, the superiority and availability of the developed design method are extensively described and validated via its application to a truck control model.

In this article, the consensus problem of linear multiagent systems (MASs) is investigated, where an event-triggered mechanism combined with sampler is introduced to rationally utilize the network bandwidth and the communication energy. Different from most existing results on the event-triggered consensus of MASs, a time-varying communication delay (CD) with a more general form is constructed in this article. With the help of a new class of Lyapunov functional and advanced inequalities, some novel criteria for achieving the asymptotic consensus of the considered MASs under different CD cases are obtained. For demonstrating the superiority of the proposed method from the conservatism and the practicability, a compared example and an application of spacecraft formation flying are proposed, respectively.

In this brief, the dynamic event-triggered control is investigated for a novel class of singularity-perturbed dynamic networks (SPDNs) with multi-time-scale. First, for a single agent, the two-time-scale characteristic described by a small singularity-perturbed parameter (SPP) is considered. Then, every agent is equipped with a personalized SPP $\varepsilon _{i}$ , which denotes the multi-time-scale characteristic of the SPDNs. Owing to the SPP $\varepsilon _{i}$ , the restriction in most the existing works that every agent must have the same SPP can be removed. Further, the networks with single-time-scale, two-time-scale, or multi-time-scale can all be modeled by the proposed SPDNs by selecting an appropriate value of $\varepsilon _{i}$ . A state feedback controller based only on the slow dynamics information is considered. Besides, a dynamic event-triggered mechanism (ETM), where the threshold parameters are adjusted as the slow state fluctuations, is introduced to reduce the communication frequency reasonably. By means of Lyapunov stability theorem and a decoupled method, some stability conditions that are independent of the scale of the SPDNs are obtained. Finally, the effectiveness and advantages of the proposed method over existing ones are demonstrated through an electronic circuit system.

In this article, the asynchronous control problem of fuzzy networked control systems (NCSs) with an efficient dynamic event-triggered (DET) strategy is studied. Particularly, an time-varying variable is designed to regulate the triggering threshold, which changes with the system error states. Different from the existing results, the proposed DET is sample-data-based, which can be exclude the Zeno behaviour naturally. In addition, to solve the mismatch induced by the DET strategy, the asynchronous controller is designed. By using the Lyapunov stability theory, some stability conditions can be obtained. Finally, an example is given to illustrate the effectiveness of the proposed method.

In numerous practical systems, the dynamics inherently involve multiple time scales. For example, in motors, power electronic, and other electrical circuits, fast electromagnetic transients coexist with slow mechanical motions. Motivated by this observation, this paper develops a two-timescale event-triggered control strategy tailored for such multi-timescale systems. To conserve communication resources, an efficient two-timescale dynamic event-triggered mechanism is designed, in which an auxiliary variable is introduced to dynamically adjust the triggering threshold, while a nonlinear function is introduced to further accelerate the convergence of the error system, balancing the system performance and bandwidth resource. On this basis, a two-timescale adaptive controller is proposed to adjust the network coupling strength, which depends on the slow-fast timescale parameters. Furthermore, by leveraging the characteristics of network topology, the consensus conditions are extended to a situation where computational complexity is independent of the number of network nodes, in which case the adaptive parameter is constant. Finally, to validate the effectiveness of the proposed method, two illustrative examples including an electric circuit network and five single-link manipulators are provided.