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Summary: This paper studies the adaptive synchronization of complex spatio‐temporal networks modeled by semi‐linear hyperbolic partial differential equations (CSTNSLHPDEs) as well as considering time‐invariant and time‐varying delays in a one‐dimensional space. Firstly, a distributed adaptive controller is proposed, where different nodes are with different adaptive gains. Secondly, four cases, CSTNSLHPDEs with time‐invariant delays and one single weight, with time‐invariant delays and multi‐weights, with time‐varying delays and one single weight, and with time‐varying delays and multi‐weights, are successively analyzed, and synchronization conditions of these four cases are obtained by using the proposed distributed adaptive controller. In the end, examples illustrate the effectiveness of the proposed distributed adaptive controller. [ABSTRACT FROM AUTHOR]

In this paper, the leader‐following consensus problem of general linear multi‐agent systems with distributed dynamic event‐triggered control is studied. A distributed controller with estimated states is designed and a dynamic event‐triggered communication protocol with an auxiliary variable is proposed for each agent to update its triggering threshold. Under this control strategy, the systems only need the states in triggering instants as a result of the utilisation of estimated states. The existence of a dynamic threshold guarantees fewer triggering times, in contrast to the conventional static one. Meanwhile, the estimator is designed between the triggering instants to reduce the state shift, the next state of each agent depends on the local information of itself and its neighbours rather than global information. Then, the multi‐agent systems can achieve consensus without Zeno behaviour. Finally, a simulation example is offered to verify the effectiveness and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the leader‐following consensus problem of general linear multi‐agent systems with distributed dynamic event‐triggered control is studied. A distributed controller with estimated states is designed and a dynamic event‐triggered communication protocol with an auxiliary variable is proposed for each agent to update its triggering threshold. Under this control strategy, the systems only need the states in triggering instants as a result of the utilisation of estimated states. The existence of a dynamic threshold guarantees fewer triggering times, in contrast to the conventional static one. Meanwhile, the estimator is designed between the triggering instants to reduce the state shift, the next state of each agent depends on the local information of itself and its neighbours rather than global information. Then, the multi‐agent systems can achieve consensus without Zeno behaviour. Finally, a simulation example is offered to verify the effectiveness and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we investigate the pinning synchronization of directed complex network with time‐varying delay under the adaptive aperiodically intermittent control. First, the model of a directed complex network is established, the interaction graph of which is not required to contain a directed spanning tree, and for which an adaptive aperiodically intermittent feedback controller is well designed. In addition, based on the Lyapunov function method and linear matrix inequality technique, several asymptotical synchronization criteria are derived via an aperiodically intermittent strategy, which is superior to the periodical scheme. Moreover, the adaptive strategy providing the exponential convergence rate and the pinning algorithm demonstrating how to select pinned nodes are presented. Finally, numerical examples are provided to illustrate the effectiveness of the derived theoretical results. [ABSTRACT FROM AUTHOR]

The target of this article is to study almost periodic dynamical behaviors for complex-valued recurrent neural networks with discontinuous activation functions and time-varying delays. We construct an equivalent discontinuous right-hand equation by decomposing real and imaginary parts of complex-valued neural networks. Based on differential inclusions theory, diagonal dominant principle and nonsmooth analysis theory of generalized Lyapunov function method, we achieve the existence, uniqueness and global stability of almost periodic solution for the equivalent delayed differential network. In particular, we derive a series of results on the equivalent neural networks with discontinuous activation functions, constant coefficients as well as periodic coefficients, respectively. Finally, we give a numerical example to demonstrate the effectiveness and feasibility of the derived theoretical results. [ABSTRACT FROM AUTHOR]

We study the finite-time stability of genetic regulatory networks with impulsive effects. Using the method of Lyapunov function, sufficient conditions of the finite-stability, in terms of linear matrix inequalities, are established. A numerical example is provided to further illustrate the significance of our results. [ABSTRACT FROM AUTHOR]

In this paper we study the quasineutral limit of the two-species Vlasov-Poisson system. For well-prepared initial data, we establish the convergence of the Vlasov-Poisson system to the pressureless Euler system as the Debye length tends to zero. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the hybrid synchronization behavior in an array of coupled chaotic systems with ring connection, of which means complete synchronization (CS) and anti-synchronization (AS) could coexist. First, the anti-synchronization controllers are designed, which can transform the synchronization error dynamic system into a nonlinear system with an antisymmetric structure. Second, we investigate the complete synchronization behavior in such a chaotic system under the anti-synchronization control. After that, the stability conditions are given for reaching hybrid synchronization. Finally, numerical examples and simulation results are presented to verify and validate the hybrid synchronization behavior in coupled chaotic system. [ABSTRACT FROM AUTHOR]

In this paper, we use an underactuated four-link gymnast robot (UFGR) with a passive first joint to model a gymnast on the bar, and consider the stabilization of the UFGR at the straight-up position. First, we introduce a coupled relationship between control torques for the UFGR. It decouples some state variables of the UFGR from others and changes the nonlinear UFGR system into a cascade-connected system. And then, we use an energy-based method to design a stabilizing controller for the zero dynamics of the cascade-connected system. And the triangle lemma guarantees the control objective of the UFGR to be achieved. The torque-coupled method transforms the stabilization of an underactuated four-link manipulator into that of an underactuated two-link acrobot. This makes the structure of the control system simple. Moreover, our proposed control strategy is easy to extend to the stabilization control of other multi-input nonlinear underactuated systems. Simulation results using the characteristics parameters of a gymnast demonstrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the center conditions and the conditions for bifurcations of limit cycles from a third-order nilpotent critical point in a class of quartic systems are investigated. Taking the system coefficients as parameters, explicit expressions for the first 11 quasi-Lyapunov constants are deduced. As a result, we prove that 11 or 12 small-amplitude limit cycles could be created from the third-order nilpotent critical point by two different perturbations. [ABSTRACT FROM AUTHOR]

This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs) with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs). With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD) state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs). Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of exponential synchronization for a class of complex spatio-temporal networks with space-varying coefficients, where the dynamics of nodes are described by coupled partial differential equations (PDEs). The goal of this research is to design distributed proportional-spatial derivative (P-sD) state feedback controllers to ensure exponential synchronization of the complex spatio-temporal network. Using Lyapunov׳s direct method, the problem of exponential synchronization of the complex spatio-temporal network is formulated as the feasibility problem of spatial differential linear matrix inequality (SDLMI) in space. The feasible solutions to this SDLMI in space can be approximately derived via the standard finite difference method and the linear matrix inequality (LMI) optimization technique. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

This article addresses the fixed-time (F-T) and predefined-time (P-T) cluster lag synchronization of stochastic multi-weighted complex networks (SMWCNs) via strictly intermittent quantized control (SIQC). Firstly, by exploiting mathematical induction and reduction to absurdity, a novel F-T stability lemma is proved and an accurate estimation of settling time (ST) is obtained. Subsequently, by virtue of the proposed F-T stability, some simple conditions that ensure the F-T cluster lag synchronization of SMWCNs are derived by developing a SIQC strategy. Furthermore, the P-T cluster lag synchronization is also explored based on a SIQC design, where the ST can be predefined by an adjustable constant of the controller. Note that the designed controllers here are simpler and more economical than the traditional design whose the linear part is still activated during the rest interval. Finally, two numerical examples are provided to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies the input-to-state stability (ISS) and the finite-time input-to-state stability issues for the discrete-time stochastic switched nonlinear systems with time-varying delay. Based on the improved vector-version comparison principle and by employing the stochastic analysis method, sufficient conditions are first derived to guarantee the discrete-time stochastic switched system to be finite-time input-to-state stable in mean and finite-time stochastic input-to-state stable. Then, the comparison principle is further utilised to establish the p-th moment ISS result. As an application, the mean-square ISS is analysed for the linear discrete-time stochastic switched system. At the end of the paper, two numerical examples are provided to illustrate the feasibility/effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Abstract: This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young’s inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks. [Copyright &y& Elsevier]

Abstract: In this paper, the global exponential stability and the existence of periodic solution are studied for a class of high-order Hopfield neural networks (HHNNs) with time delays by employing Lyapunov method and linear matrix inequality (LMI) technique. Several simple sufficient conditions are given ensuring global exponential stability and the existence of periodic solution of HHNNs. The obtained results improve some previous works and do not require the symmetry of weight matrix. Finally, two illustrative examples are given to demonstrate the effectiveness of the obtained results. [Copyright &y& Elsevier]

Abstract: This paper investigates the global exponential synchronization of delay-coupled identical genetic oscillator. By constructing appropriate Lyapunov functional and using the linear matrix inequality (LMI) approach, a series of sufficient criteria, which are very easy to verify, are obtained. It is shown that these criteria improve and extend the earlier works. Finally, a population of genetic oscillators based on the Goodwin model is adopted as a numerical example to demonstrate the effectiveness of our theoretical results. [Copyright &y& Elsevier]

Abstract: In this paper, the exponential stability of a two-species competitive Lotka–Volterra system with discrete delays has been studied. By constructing appropriate Lyapunov functional and using the linear matrix inequality (LMI) optimization approach, a series of sufficient criteria is obtained which ensure the exponential stability of the positive equilibrium of the given Lotka–Volterra system. The results are new and improve some earlier work. An illustrative example is given to demonstrate the effectiveness of the obtained results. [Copyright &y& Elsevier]

Abstract: This paper considers the problems of global exponential stability and exponential convergence rate for impulsive neural networks with time-varying delays and reaction–diffusion terms. By using Lyapunov functions method, some sufficient conditions ensuring global exponential stability of the networks are derived, and the estimated exponential convergence rate is also obtained. A numerical example is given at the end of this paper to demonstrate the effectiveness and applicability of the proposed criteria. [Copyright &y& Elsevier]

This article considers the design problem of H∞$$ {H}_{\infty } $$ observer‐based fault‐tolerant control under three faulty cases: sensor only, actuator only, and both sensor and actuator faults. To save communication resources, the event trigger mechanism method is used for sensor‐to‐observer and observer‐to‐controller transmissions. In this case, the design method of the new H∞$$ {H}_{\infty } $$ observer is given for obtaining estimating both states and faults which are used to design observer‐based H∞$$ {H}_{\infty } $$ fault‐tolerant controllers. In particular, the virtual observer is designed to suppress the effects of faults on the system. As the virtual observer contains unmeasurable system information, the real observer is built on top of the virtual observer to eliminate the unmeasurable information. Finally, the feasibility of the approach is tested with a numerical example. [ABSTRACT FROM AUTHOR]

This study addresses the fixed/preset-time bipartite synchronization (FTBS/PTBS) of memristor-based discontinuous multi-layer signed networks via quantized dynamic event-triggered control (ETC). Firstly, a memristor-based neural network model incorporating multi-layer coupling structures, signed networks and discontinuous activations is built. Subsequently, by designing two quantized dynamic ETC strategies without the linear feedback term, the FTBS and PTBS of the considered networks are discussed, and it is proved that Zeno behavior can be ruled out. In contrast to the previous static ETC mechanism, the introduced internal dynamic variable can significantly decrease the triggering times and further save communication resources. Lastly, three numerical examples are offered to verify the correctness and practicability of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper considers the finite‐time synchronization problem of complex networks with hybrid‐coupled time‐varying delay. We combine aperiodically intermittent pinning control method and event‐triggered control method to design the controller, which can guarantee that the states of all nodes can realize synchronization in the finite‐time. The event‐triggered mechanism is introduced according to the difference of error values between nodes and reduces the communication frequency. Besides, the pinning nodes are reselected at each triggered moment by a given algorithm. Based on the appropriate inequality scaling technique and Lyapunov function, the finite‐time synchronization criteria are obtained for the given network system model. Finally, the feasibility of the theoretical results is proved through a simulation example. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed event-triggered control problems of second-order nonlinear multi-agent systems (MASs) with directed graph. Firstly, an event-triggered consensus algorithm is developed for second-order nonlinear MASs. It is proved that MASs reach practical consensus and Zeno-behavior doesn't occur. Secondly, for leader–follower MASs, an event-triggered tracking algorithm is presented, which ensures that follower agents track leader agent even when leader agent has a nonzero input. Finally, a numerical simulation is given to show effectiveness of the proposed consensus algorithm. [ABSTRACT FROM AUTHOR]

This article concerns the fixed-time (FET) and prescribed-time (PET) synchronization of quaternion-valued fuzzy BAM neural networks via aperiodic intermittent pinning control. First of all, two improved inequalities for FET and PET stability are proposed to reduce the conservatism of existing results in theoretical analysis. Subsequently, by excluding the control input of the rest interval in previous semi-intermittent design, two novel quaternion-valued aperiodic intermittent pinning controllers are developed. Furthermore, regarding the original quaternion-valued networks as an entirety instead of decomposing it into four real-valued subnetworks, several sufficient criteria that ensure the FET and PET synchronization of quaternion-valued fuzzy BAM neural networks are obtained by means of the improved stability inequalities and the designed controllers. Finally, the validity of the theoretical results is verified by three numerical examples. [ABSTRACT FROM AUTHOR]

• This work proposes MPFFPSDC, a novel deep learning algorithm based on multi-pooling feature fusion for DDS prediction. • In MPFFPSDC, we introduce a new pooling method, which uses attention mechanism to aggregate atomic feature vectors into a drug feature vector. • MPFFPSDC can keep maintain the symmetry of drug inputs to eliminate the inconsistency of predictive results caused by different drug input sequences. • Compared with existing state-of-the-art methods, MPFFPSDC achieves higher predictive accuracy. Drug combination therapies are common practice in the treatment of cancer, but not all combinations result in synergy. As traditional screening approaches are restricted in their ability to uncover synergistic drug combinations, computer-aided medicine is becoming a increasingly prevalent in this field. In this work, a predictive model of potential interactions between drugs named MPFFPSDC is presented, which can maintain the symmetry of drug inputs and eliminate inconsistencies in predictive results caused by different drug inputting sequences or positions. The experimental results show that MPFFPSDC outperforms comparative models in major performance indicators and exhibits better generalization for independent data. Furthermore, the case study demonstrates that our model can capture molecular substructures that contribute to the synergistic effect of two drugs. These results indicate that MPFFPSDC not only offers strong predictive performance, but also has good model interpretability that may provide new insights for the study of drug interaction mechanisms and the development of new drugs. [ABSTRACT FROM AUTHOR]

This paper is devoted to work out a stabilized controller by state feedback for a class of nonlinear systems. In this paper, we not only extend the existing results that system has a single power term to the case with multiple coupling power terms, but also consider that the power is time varying, which makes the system studied in this paper more general than that in other literature. By the backstepping method, a linear easy-to-implement controller is designed, which not only ensures the stability of the system but also has a good convergence speed. Finally, with a representative numerical example, by calculating all the parameters in the design procedure, the simulation shows that all the responses of the states and the controller are asymptotically stable at the equilibrium zero, which verifies the effectiveness of the control design scheme of this paper. [ABSTRACT FROM AUTHOR]

This paper focuses on exponential synchronization for master–slave time-varying delayed complex-valued neural networks (CVNNs) under hybrid impulsive controllers. Hybrid impulsive controllers is the extension of impulsive controllers, which can simultaneously permit synchronizing as well as desynchronizing impulses in one impulsive sequence, i.e., hybrid impulses. We separate CVNNs into their real and imaginary parts, which leads to two real-valued neural networks (RVNNs). Based on the concepts of average impulsive interval (AII) and average impulsive gain (AIG), we find that master–slave exponential synchronization for the real and imaginary parts of CVNNs can be realized via hybrid impulsive control under certain conditions. By employing the Lyapunov method, sufficient criteria are established to guarantee synchronization of the given master–slave CVNNs. Finally, the validity of the obtained results is demonstrated via a numerical example. [ABSTRACT FROM AUTHOR]

Summary: A cart‐pendulum system is a nonlinear underactuated mechanical system with two degrees of freedom. This paper addresses the motion trajectory design and tracking control problems for this underactuated system. First, a friction‐like control law is designed for the system. Then, the characteristics of the closed‐loop control system are analyzed. Second, a new method of constructing an optimal trajectory for the system is developed. Then, a tracking control law is designed to quickly track the constructed trajectory. It guarantees that the motion control of the cart‐pendulum system is achieved along a reference trajectory. Finally, a numerical example is presented to demonstrate the effectiveness of the theoretical results. This study constructs an optimal trajectory for the cart‐pendulum system in its whole motion space and solves the motion control objective by tracking the constructed trajectory. It has many advantages compared with other motion control methods, eg, the optimal motion control objective of the system is achieved by a single control law; and the motion process and transient characteristics (eg, the settling time) of the control system can be accurately predicted. [ABSTRACT FROM AUTHOR]

A translational oscillator with a rotational actuator (TORA) is an underactuated mechanical system with two degrees of freedom. This paper presents a new method to solve the global stabilisation control problem for this underactuated system. First, a set of suitable state variables is chosen for the TORA. It transforms the system into a cascade affine nonlinear system. Then, a positive-definite Lyapunov function is constructed based on the structural characteristics of the system. A control law is designed to guarantee that the derivative of the Lyapunov function is non-positive. Finally, the global stability of the closed-loop control system is analysed using the Lasalle invariance principle. The condition on the control parameters is presented to globally stabilise the TORA at the origin. The effectiveness and robustness of the method are verified by a numerical example. [ABSTRACT FROM AUTHOR]

This paper addresses the problem for output synchronization of a class of complex networks (CNs) with reaction-diffusion terms and input constraint. Without considering input constraint, proportional-spatial derivative (P-sD) control of the CN is firstly studied, and then, the problem of output synchronization of CN is formulated as the feasibility problem of linear matrix inequalities (LMIs). Based on the obtained results, considering P-sD control with input constraint, output synchronization is then studied and formulated as the feasibility problem of LMIs and spatial algebraic linear matrix inequalities (SALMIs). In the end, numerical simulation shows the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

• The stochastic complex networks model with internal and coupled delays is established. • The pinning impulsive controller without sign function is designed to achieve finite-time synchronization. • A unified finite-time synchronization criterion is derived under synchronizing impulses and desynchronizing impulses. • The pinned nodes are related to the error values of the nodes, which improves the utilization of control resources. This paper mainly considers the finite-time synchronization (FTS) of stochastic complex networks with mixed delays via pinning impulsive control. Firstly, a novel pinning impulsive controller is introduced by selecting the nodes of the stochastic complex network with large error norms, which not only saves control resources, but also ensures that stochastic complex network with mixed delays can realize FTS. It is worth noting that the finite-time control strategy constructed is not affected by the sign function. Secondly, a uniform FTS criterion under synchronizing impulses and desynchronizing impulses is derived based on the idea of average impulsive interval. Moreover, the obtained sufficient condition are further extended to general stochastic complex networks and stochastic complex networks with mixed delays under delayed impulses. Finally, the feasibility of the theory results is verified by a numerical example. [ABSTRACT FROM AUTHOR]

A cart‐double pendulum system is an underactuated mechanical system that has three degrees of freedom (DOF) and has two actuators. This paper discusses the stabilizing control problem for this non‐linear mechanical system. First, an input relationship is constructed to transform the 3‐DOF cart‐double pendulum system into a 2‐DOF reduced‐order system in a fixed time. Second, a swing‐up controller is designed for the reduced‐order system to make the system infinitely approach upright equilibrium point. After that, the swing‐up controller switches to a fixed‐time balance stabilization controller, which stabilizes the cart‐double pendulum at the upright equilibrium point in a fixed time. Finally, numerical examples verify the effectiveness of this presented control strategy. [ABSTRACT FROM AUTHOR]

In this paper, the bipartite consensus problem for second-order multi-agent systems with no leader, one leader and multiple leaders are investigated, where the information exchange is disturbed by measurement noise and antagonistic information. In order to attenuate the effect of communication noise, a time-varying gain c (t) is utilized and the stochastic approximation bipartite control protocol is proposed. It is given that the underlying protocol can solve the bipartite consensus problem for MASs with no leader/one leader/multiple leaders if the communication topology is strongly connected/has a spanning tree/has a spanning forest and the c (t) satisfies some mild condition. Meanwhile, for system with these three cases, a series of sufficient and necessary conditions are given. Especially, for the case with no leader, we obtain that the final state of agent is related with the initial position and initial velocity of each agent. For the case with one leader, we can get that the followers in one group can follow up the state of one leader, and the followers in another group tend to the opposite value. Additionally, for the case with multiple leaders, the containment control can be achieved where followers' states in one group can converge to the quai-convex hull of leaders' state and the ones in another group converge to the opposite convex hull. Finally, some numerical examples are given to support our new results. [ABSTRACT FROM AUTHOR]

With the rapid growth of the Internet, a wealth of movie resources are readily available on the major search engines. Still, it is unlikely that users will be able to find precisely the movies they are more interested in any time soon. Traditional recommendation algorithms, such as collaborative filtering recommendation algorithms only use the user's rating information of the movie, without using the attribute information of the user and the movie, which has the problem of inaccurate recommendations. In order to achieve personalized accurate movie recommendations, a movie recommendation algorithm based on a multi-feature attention mechanism with deep neural networks and convolutional neural networks is proposed. In order to make the predicted movie ratings more accurate, user attribute information and movie attribute information are added, user network and movie network are presented to learn user features and movie features, respectively, and a feature attention mechanism is proposed so that different parts contribute differently to movie ratings. Text features are also extracted using convolutional neural networks, in which an attention mechanism is added to make the extracted text features more accurate, and finally, personalized movie accurate recommendations are achieved. The experimental results verify the effectiveness of the algorithm. The user attribute features and movie attribute features have a good effect on the rating, the feature attention mechanism makes the features distinguish the degree of importance to the rating, and the convolutional neural network adding the attention mechanism makes the extracted text features more effective and achieves high accuracy in MSE, MAE, MAPE, R2, and RMSE indexes. [ABSTRACT FROM AUTHOR]

This article studies the simultaneous fault‐tolerant control and disturbance rejection for systems with fault in polynomial form. The unknown external disturbance is considered to be caused by the external source system, and the fault can be expressed as a polynomial function of time. Combining the fault observer and the disturbance observer, a controller is designed, which can not only diagnose the fault, but also improve the anti‐disturbance performance. Finally, a numerical example is given to verify the validity of the results. [ABSTRACT FROM AUTHOR]

This paper investigates the synchronization of multiple chaotic systems with unknown parameters using adaptive control method, and two kinds of different synchronization modes are considered here. One is that more response systems synchronize with one drive system, and the other is the ring transmission synchronization, which guarantees that all chaotic systems can synchronize with each other. The definition of adaptive synchronization of multiple chaotic systems with unknown parameters is given, and then based on the idea of adaptive control method, adaptive laws are derived to estimate the unknown parameters, and nonlinear adaptive controllers are developed to ensure the asymptotical stability of two classes of error systems. Finally, simulation results are presented to verify the effectiveness of proposed synchronization schemes. [ABSTRACT FROM AUTHOR]

In this study, a new learning control scheme is designed to investigate the stability of a multilayer supply chain network (SCN) and to further improve the convergence speed of the nodes’ states of such a multilayer SCN. Specifically, a multilayer SCN model with three layers is first established and some practical constraints on the states of the proposed SCN model are involved and discussed. By taking the quantities of goods transmitted between different nodes as control inputs, a new kind of learning control scheme is subsequently proposed to discuss the stability of the nodes’ states within the SCN. It is further shown that the convergence speed of nodes’ states with this scheme is faster than that yielded by using some traditional schemes. The contributions of our scheme are twofold: 1) it can save the limited control resource and 2) it can improve the convergence speeds of the states of all nodes. Numerical simulations are finally given to illustrate the effectiveness and advantages of the designed learning scheme. [ABSTRACT FROM AUTHOR]

Summary: This article studies the adaptive control for synchronization of semi‐linear complex spatio‐temporal networks (CSNs). And the leader‐following and leaderless CSN with time‐invariant coupling delay and time‐variant coupling delay are developed separately from two aspects. The adaptive control strategies are proposed to reach the asymptotic convergence of synchronization error. Synchronization criteria and sufficient conditions are obtained for the leader‐following CSN error model and leaderless CSN error model by constructing the apposite Lyapunov–Krasovskii functions and applying Wirtinger's inequality. Finally, two experimental examples are given to verify the feasibility of the theories proposed in this article. [ABSTRACT FROM AUTHOR]

Finite-time synchronization (FTS) of uncertain fractional-order memristive neural networks (FMNNs) with leakage and discrete delays is studied in this paper, in which the impacts of uncertain parameters as well as external disturbances are considered. First, the fractional-order adaptive terminal sliding mode control scheme (FATSMC) is designed, which can effectively estimate the upper bounds of unknown external disturbances. Second, the FTS of the master–slave FMNNs is realized and the corresponding synchronization criteria and the explicit expression of the settling time (ST) are obtained. Finally, a numerical example and a secure communication application are provided to demonstrate the validity of the obtained results. [ABSTRACT FROM AUTHOR]