This paper delves into the state estimation and finite-time (FT) synchronization for fractional neural networks with time delayed. Firstly, a Luenberger observer is proposed to estimate the unknown state. Secondly, the controller with sign or saturation functions is designed to achieve FT synchronization, which the saturation functions is utilized to avoid chattering phenomenon. Correspondingly, several algebraic-form-based synchronization criteria and the setting times are presented by means of the Jensen inequality, fractional-order Razumikhin theorem and fractional-order calculus property. Finally, two examples are listed to illustrate the correctness of the adopted approaches.

This paper focuses on the finite-time projective synchronization (FTPS) of fractional fuzzy inertial delayed neural networks (FFIDNNs) with parameters perturbation via several quantified event-triggered mechanisms (QETMs). First, applying Laplace transform, a linear fractional finite-time inequality is established for the infinite time interval rather than a finite time interval. Next, three kinds of QETMs are designed, which can respond flexibly to practical challenges. By the established inequalities and the designed controller, some novel criteria are derived to guarantee FTPS for the considered system. Moreover, the settling time is estimated and the event interval has a positive lower bound to avoid the Zeno behavior. Finally, the accuracy of theoretical findings is confirmed via numerical examples.

In this article, we tackle the problem of analyzing dissipativity, via devising switching mechanisms, for switched positive Takagi–Sugeno (T–S) fuzzy systems with time-varying delay. To leverage the positivity properties of state, input, and output variables, a novel concept of dissipativity is developed, focusing on linear supply rates and linear copositive storage functionals. When state information is available, the state dependent switching mechanism satisfying a dwell time constraint is introduced dependent on the constructed time-varying multiple linear copositive storage functionals. This mechanism allows for solving the dissipativity issue for the entire system without imposing any solvability requirements on subsystems and reduces the switching frequency. In cases, where state information is unavailable, dissipativity is ensured by a dwell-time dependent switching mechanism. Further, all conditions guaranteeing the solvability of the problem are presented in the form of linear vector inequalities. Two simulation examples are finally offered, demonstrating that the proposed techniques are effective and superior.

This article develops pinning control strategies to achieve global asymptotic stabilization in large-scale Markovian jump Boolean networks (MJBNs), closely linking their stability to network structural characteristics. First, the considered MJBN is divided into several sub-MJBNs, where signals switch according to irreducible transition probability matrices. Second, the stability of these sub-MJBNs is mapped onto that of deterministic periodic BNs. This transformation facilitates the formulation of a network-structure-based stability criterion for MJBNs by converting the inherently random stability characteristics of the networks into those of deterministic networks. Third, applying this criterion, static pinning control (SPC) is devised to stabilize MJBNs, where effective pinning nodes are identified by finding a feedback vertex set in the correspondingn-vertex digraph. Consequently, this method addresses the challenges associated with large-scale MJBNs effectively. To demonstrate the practical applicability of our theoretical findings, two biological examples are presented.

In this article, fault detectability of Boolean control networks (BCNs) is analyzed via a labeled graph approach. First, matrix-based representations of nonfault BCNs and fault BCNs are constructed by using the semi-tensor product (STP) of matrices. Based on these matrix representations, labeled graphs are further developed for nonfault BCNs and fault BCNs, respectively. Then, the passive fault detectability (PFD) is solved by labeled graph of the nonfault BCN. Meanwhile, based on the labeled graphs of nonfault BCNs and fault BCNs, the active fault detectability (AFD) is further studied. By leveraging labeled graphs, two sufficient criteria for strong AFD and AFD can be derived without the need for iterative matrix calculations, thereby significantly reducing computational complexity. Furthermore, the corresponding necessary and sufficient criteria are further derived when these two sufficient criteria are invalid. Finally, a biological system for the lac operon in$Escherichia~coli$is elaborated to verify the effectiveness of obtained results.

This technical paper investigates the cluster synchronization of finite-field networks (FFNs) based on the algebraic state space representation. By resorting to the semi-tensor product of matrices, the cluster synchronization of an FFN can be completely converted into the set stability of state trajectory. Then, a necessary and sufficient condition for the cluster synchronization of FFNs is obtained based on the invariant subset and one-step transition matrix. In particular, the obtained results are applicable to check the leader-follower synchronization and group consensus of FFNs. Finally, a numerical example is given to illustrate the feasibility of the obtained results.

Emerging technologies of connected and automated vehicles (CAVs) applied at intersections have great potential to improve traffic efficiency, driving safety, and fuel economy. This paper proposes a virtual spring strategy for coordinating CAVs to pass through signal-free intersections. A virtual spring coordination system (VSCS) is established to force the movements of conflicting CAVs in terms of spring characteristics. Inspired by the properties of springs with dampers, a distributed control protocol is designed to regulate CAVs to reach a desired state of motion when crossing intersections. For ensuring the convergence of the VSCS, i.e., the total elastic potential energy approaches to zero, sufficient conditions for the internal stability are derived subject to the input saturation. To further improve the anti-disturbance capability of the VSCS, we ensure the upper bound of the disturbance propagation, which is characterized by an$H_{\infty }$performance index. The proposed strategy is developed in a receding horizon framework and tested under the two scenarios in simulations. The simulation results show the effectiveness and superiority of the proposed strategy.

Finite/fixed-time controls for multiagent systems (MASs) in cooperative and competitive networks have been discussed intensively, and the structural balance and gauge transformation play a crucial role in analyzing the finite/fixed-time bipartite cooperative behavior of MASs. However, the structural balance for a large-sized network is not easy to verify, and it is uncertain whether the gauge transformation is feasible for nonlinear networks. Without adopting the gauge transformation, this article considers finite/fixed-time bipartite controls of nonlinear neural networks (NNs) with cooperative and competitive interactions. A matrix$M$in cooperative networks is extended to a general one in cooperative and competitive networks to design quadratic Lyapunov functions. On this basis, the finite/fixed-time bipartite synchronization criteria and adjustment times are obtained, which avoids adopting the gauge transformation in a nonlinear system. The negative cycle is found to have a very important effect on the dynamic behavior of NNs. Numerical examples validate the proposed bipartite controls of NNs in a signed graph.

This article investigates the intermittent event-triggered optimal leader-following consensus for nonlinear multi-agent systems (MASs) utilizing the actor-critic algorithm. First, we propose a novel distributed intermittent event-triggered control strategy, and a sufficient criterion is obtained to guarantee the leader-following consensus of MASs by establishing a novel piecewise differential inequality. Next, the intermittent event-triggered optimal control strategy is delicately given. Remarkably, the optimality of MASs is proven based on policy iteration and the convergence of the closed-loop system is also proved based on the Lyapunov stability theory. Then, the intermittent event-triggered approximate optimal control strategy is designed via an actor-critic network whose weights are only updated at the trigger instants. Furthermore, the Zeno behavior can be excluded in this article. Finally, two simulation examples further verify the effectiveness of the proposed scheme.

This article studies the minimal reconstructibility of Boolean control networks (BCNs) based on the semi-tensor product (STP). Two effective criteria for the reconstructibility of BCNs under two definitions are proposed by using weak control invariant subset (WCIS) and strong control invariant subset (SCIS). By injecting new measurements, a minimal reconstructibility problem (MRP) is established for achieving reconstructibility. Based on constructing an index matrix, the solution of the MRP is transformed into the solution of the equation. Finally, a biological example is given to illustrate the theoretical results and further emphasize the inequivalence of the two definitions.

The time-triggered impulsive control of complex homogeneous dynamical networks has received wide attention due to its occasional occupation of the communication channels. This article is devoted to quasisynchronization of heterogeneous dynamical networks via event-triggered impulsive controls with less channel occupation. Two kinds of triggered mechanisms, that is, the centralized event-triggered mechanism in which the control is updated based upon the state information of all nodes, and the distributed event-triggered mechanism where the control is updated according to the state information of each node and its neighboring node, are proposed, respectively, such that the synchronization error between the heterogeneous dynamical networks and a virtual target is not more than a nonzero bound. What is more, the Zeno behavior is shown to be excluded. It is found that the combination method of the event-triggered control and the impulsive control, that is, the distributed event-triggered impulsive control has the advantage of low-energy consumption and takes up many fewer communication channels over the time-triggered impulsive control. Two numerical examples are conducted to illustrate the effectiveness of the proposed event-triggered impulsive controls.

This article deals with the exponential synchronization problem for complex dynamical networks (CDNs) with coupling delay by means of the event-triggered delayed impulsive control (ETDIC) strategy. This novel ETDIC strategy combining delayed impulsive control with the event-triggering mechanism is formulated based on the quadratic Lyapunov function. Among them, the event-triggering instants are generated whenever the ETDIC strategy is violated and delayed impulsive control is implemented only at event-triggering instants, which allows the existence of some network problems, such as packet loss, misordering, and retransmission. By employing the Lyapunov-Razumikhin (L-R) technique and impulsive control theory, some sufficient conditions with less conservatism are proposed in terms of linear matrix inequalities (LMIs), which indicates that the ETDIC strategy can guarantee the achievement of the exponential synchronization and eliminate the Zeno phenomenon. Finally, a numerical example and its simulations are presented to verify the effectiveness of the proposed ETDIC strategy.

This paper is concerned with the topological structure, reachability, and stabilization for Boolean control networks (BCNs) with state constraints via event-triggered control (ETC) scheme. In the first part, the topological structure of BCNs with state constraints is studied. Under the framework of state constrain, the definitions of fixed point and cycle are first defined. A novel phenomenon is that there may exist two kinds constrained fixed points, which are, respectively, named as the livelock and deadlock ones. It is different with the traditional fixed point. Accordingly, a formula is presented to calculate the number of constrained fixed points and constrained cycles. In the second part, the constrained reachability and stabilization problem of the event-triggered controlled BCNs are investigated. Two necessary and sufficient criteria are, respectively, obtained. Furthermore, an algorithm is developed to design all feasible controllers. Finally, a reduced model of the lac operon in the Escherichia coli is shown to illustrate the efficiency of the obtained results.

In this paper, we propose a novel class of networks named as quaternion-valued inertial memristor-based neural networks (QVIMNNs) by introducing inertial term and memristor into traditional quaternion-valued neural networks (QVNNs). The problem of fixed-time synchronization of the QVIMNNs is investigated based on the variable transformation and Lyapunov functional method. It is shown that two types of activation functions are considered and a novel criteria guaranteeing fixed-time synchronization for each cases are then achieved by designing different types of controllers. This paper attempts to pave a new way to investigate neural networks classes with numerical simulations support to demonstrate the correctness of the obtained results.

This article studies the event-triggered stochastic synchronization problem for neutral-type semi-Markovian jump (SMJ) neural networks with partial mode-dependent additive time-varying delays (ATDs), where the SMJ parameters in two ATDs are considered to be not completely the same as the one in the connection weight matrices of the systems. Different from the weak infinitesimal operator of multi-Markov processes, a new one for the double semi-Markovian processes (SMPs) is first proposed. To reduce the conservative of the stability criteria, a generalized reciprocally convex combination inequality (RCCI) is established by the virtue of an interesting technique. Then, based on an eligible stochastic Lyapunov-Krasovski functional, three novel stability criteria for the studied systems are derived by employing the new RCCI and combining with a well-designed event-triggered control scheme. Finally, three numerical examples and one practical engineering example are presented to show the validity of our methods.