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This paper considers an adaptive neural preassigned-time tracking control scheme for non-strict feedback stochastic nonlinear systems subjected to output constraint. Depending on the prescribed performance control idea, the output constraint is resolved. Meanwhile, combined with backstepping control scheme, the novel preassigned-time tracking controller is developed, which can not only make the system output satisfy the constraint condition, but also the track error is constrained within a preassigned region in a finite time, where the settling time is arbitrarily set and independent of any parameters. Furthermore, all signals are semi-globally uniformly ultimately bounded in the closed-loop system. Finally, the validity of the proposed control scheme is demonstrated via the practical one-link manipulator. [ABSTRACT FROM AUTHOR]

The paper addresses the fixed-/preassigned-time synchronization of stochastic memristive neural networks (MNNs) with uncertain parameters and mixed delays. Adaptive sliding mode control (ASMC) technology is mainly utilized. First, a proper sliding surface is constructed and the adaptive laws are given. Also, the synchronization control scheme is designed, which can ensure error system to realize fixed-time stability. Second, preassigned-time sliding mode control scheme is mainly provided to realize fast synchronization of MNNs. The presented theoretical methods can guarantee the error system convergence and stability for reaching and sliding mode within preassigned-time. And the synchronization criteria and explicit expression of settling time (ST) are acquired, where ST is not related with initial values and controller parameters but can be predefined perferentially. Finally, the calculation example is offered to interpret the practicability and availability of the innovations in this paper. [ABSTRACT FROM AUTHOR]

This article is concerned with sampled-data synchronization problem of heterogeneous delays inertial neural networks (INNs) with generally uncertain semi-Markovian (GUSM) jumping. Different from traditional Markovian inertial neural networks (MINNs), the INNs with GUSM are investigated in this paper by fully considering the sojourn time and the lacking transition rates, which is more general and applicable for practical system. The new extended two-sided looped-functional (ETSLF) approach is adopted in this paper, and some improved less conservative criteria are derived to achieve the synchronization of the drive and response INNs. The controller gain matrices are acquired based on synchronization criteria. Finally, the viability of the method is presented through three examples. [ABSTRACT FROM AUTHOR]

This paper focuses on event‐triggered sampled‐data synchronization of uncertain complex networks with time‐varying coupled delays. First of all, a discrete event‐triggered sampled‐data control scheme is adopted, which not only makes the state of the system be monitored in discrete time, but also the sampling information is effectively transmitted. The proposed event‐triggered mechanism effectively prevents Zeno behavior. In addition, we also use some novel piecewise time‐dependent Lyapunov–Krasovskii and Wirtinger inequality to handle the time‐varying delays and parameter uncertainties of complex networks. Then, synchronization criteria are given for uncertain complex networks. Finally, the simulation results show that the control scheme can significantly reduce the number of transmitted signals while maintaining the uncertain complex networks synchronization. [ABSTRACT FROM AUTHOR]

Falls are the main cause of increased morbidity and mortality in the elderly. Human activity recognition is a difficult task due to factors such as light changes and complex background. To address these challenges, this paper proposes a method for recognizing falling activity based on the human skeleton and optical flow sequence. First, videos of fall activities and not-fall activities of different testers are captured using the Kinect v2 sensor; then, the captured videos are pre-processed to obtain the skeleton images and grayscale images of each activity; and the optical flow sequences of adjacent images are obtained using the dense optical flow algorithm. This paper proposes a lightweight convolutional neural network for extracting movement features from multimodal data and identifying activities. The decision fusion algorithm combines the fuzzy comprehensive evaluation method and the majority voting strategy to determine the weight values that influence the final decision outcomes. The experimental results show that the accuracy of the method proposed in this paper is up to 95.31%, which has a good effect on the recognition of falling activity. [ABSTRACT FROM AUTHOR]

Gait recognition is significant in the fields of disease diagnosis and rehabilitation training by studying the characteristics of human gait with different terrain. To address the problem that the transformation of different outdoor terrains can affect the gait of walkers, a gait recognition algorithm based on feature fusion with attention mechanism is proposed. First, the acceleration, angular velocity and angle information collected by the inertial measurement unit is used; then the acquired inertial gait data is divided into periods to obtain the period data of each step; then the features are extracted from the data, followed by the visualization of the one-dimensional data into two-dimensional images. A lightweight model is designed to combine convolutional neural network with attention mechanism, and a new attention mechanism-based feature fusion method is proposed in this paper for extracting features from multiple sensors and fusing them for gait recognition. The comparison experimental results show that the recognition accuracy of the model proposed in this paper can reach 89 % , and it has good recognition effect on gait under different terrain. [ABSTRACT FROM AUTHOR]

This paper discusses the complex dynamic behavior of a novel chaotic system, which was firstly established by introducing a memristor into a similar Chen's system. Then by choosing a as the key parameter, we analyze the stability of memristor system based on eigenvalue theory. It is also found that when a cross some critical values, the system can exhibit Neimark–Sacker bifurcation and chaos behaviors. Some numerical simulations including phase diagrams and maximum Lyapunov exponent graph of the memristor-based systems are presented to verify the existence of chaos attractors. Finally, to make the results of this paper useful in the actual situation, such as the design of chaos security algorithm, analog electronic circuit of memristor chaotic system is designed. [ABSTRACT FROM AUTHOR]

Under the event-triggered scheme, this note focuses on the problem of finite-time stability analysis of the switched system with controller failure and external interference. Firstly, in order to save network communication resources, the mixed event-triggered condition is considered. This mechanism can not only avoid Zeno phenomenon, but also use the sampled information more effectively. In addition, the saturation characteristics of the actuator are fully considered, which can further reduce the number of triggers. According to different event-triggered conditions, an algorithm is proposed to estimate the attraction domain. Then, through the Lyapunov-Krasovskii functional approach and average dwell time technology, the closed-loop switched system is analyzed. The determination condition of finite-time stability is obtained. To illustrate the advantages of our established results, a numerical example is finally given. In addition to saving communication resources, the system stability is guaranteed. The advantages of the proposed method can be verified by simulation. [ABSTRACT FROM AUTHOR]

This paper investigates the cooperative state feedback control problem for delta operator-based large-scale systems with independent subsystems. First, the state feedback controller is introduced to interconnect the adjacent subsystems into a closed-loop system. Second, the Lyapunov function in delta domain is constructed, and the linear matrix inequality method is used to design the cooperative state feedback stability controller for the whole large-scale interconnected system. Third, a performance index is introduced for the design of the optimal cooperative state feedback controller. Finally, stability of the closed-loop system is proved on the basis of stability theory, and simulation examples are given for showing the effectiveness of the design method. [ABSTRACT FROM AUTHOR]

This paper investigates the finite‐time H∞$$ {H}_{\infty } $$ control of Itô‐type stochastic nonlinear systems. Considering the transient performance and anti‐interference ability within a given limited time interval, the control strategy of stochastic nonlinear systems is researched. A new sufficient condition for mean‐square finite‐time boundedness for stochastic nonlinear system is developed. Due to the state components are not available, a state observer is designed. Based on the estimated state, an H∞$$ {H}_{\infty } $$ controller is proposed and Linear Matrix Inequality (LMI) conditions are given, which not only guarantee the mean‐square finite‐time boundedness but also satisfy the corresponding H∞$$ {H}_{\infty } $$ performance. Finally, two examples are given to demonstrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

Considering the media coverage and age‐dependent education, a deterministic and a stochastic class‐age‐structured rumor propagation models are studied, respectively. First, the deterministic rumor propagation model is characterized by a coupled system of ordinary and partial differential equations. The positivity and boundness of solutions are proved, and the basic reproduction number is derived. Second, the stochastic rumor propagation model is formulated by stochastic differential equations. The existence of global positive solutions in model is discussed with the Itô's formula and stochastic Lyapunov function. Additionally, by utilizing comparison principle of stochastic differential equations and the strong law of large numbers, several sufficient conditions for extinction and persistence of the rumor are derived. Finally, numerical simulations are carried out for illustrating the results. [ABSTRACT FROM AUTHOR]

The remarkable development of human–computer interactions has created an urgent need for machines to be able to recognise human emotions. Human motions play a key role in emphasising and conveying emotions to meet the complexity of daily application scenarios, such as medical rehabilitation and social education. Therefore, this paper aims to explore hidden emotional states from human motions. Accordingly, we proposed a novel approach for emotion recognition using multiple inertial measurement unit (IMU) sensors worn on different body parts. First, the mapping relationship between emotion and human motion was established through fuzzy comprehensive evaluation, and data were collected for six emotional states: sleepy, bored, excited, tense, angry, and distressed. Second, the preprocessed data were used as input in a lightweight convolutional neural network to extract discriminative features. Third, an attention‐based sensor fusion module was developed to obtain the importance scores of each IMU sensor for generating a fused feature representation. In the recognition phase, we constructed a weighted kernel support vector machine (SVM) model with an auxiliary fuzzy function to improve the weight calculation method of kernel functions in a multiple kernel SVM. Finally, the results obtained are compared with those of similar state‐of‐the‐art studies, the proposed method showed a higher accuracy (99.02%) for the six emotional states mentioned above. These findings may promote the development of social robots with non‐verbal emotional communication capabilities. [ABSTRACT FROM AUTHOR]

This paper considers the finite-time synchronization problem of stochastic complex networks with mixed delays. A controller based on adaptive aperiodic intermittent control strategy is constructed, which can guarantee that network systems with unknown characteristics of the controlled object or a wide range of disturbance characteristics achieve synchronization in the finite-time. Moreover, relying on various inequality techniques, the finite-time synchronization criterion is obtained by establishing the Lyapunov function. Then, the synchronization of the stochastic network system can still be achieved, when the stochastic disturbance does not exist. Finally, the rationality of the theoretical results is tested by an example of Chua's circuit system. [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]

Low-illumination image enhancement can provide more information than the original image in low-light scenarios, e.g., nighttime driving. Traditional deep-learning-based image enhancement algorithms struggle to balance the performance between the overall illumination enhancement and local edge details, due to limitations of time and computational cost. This paper proposes a histogram equalization–multiscale Retinex combination approach (HE-MSR-COM) that aims at solving the blur edge problem of HE and the uncertainty in selecting parameters for image illumination enhancement in MSR. The enhanced illumination information is extracted from the low-frequency component in the HE-enhanced image, and the enhanced edge information is obtained from the high-frequency component in the MSR-enhanced image. By designing adaptive fusion weights of HE and MSR, the proposed method effectively combines enhanced illumination and edge information. The experimental results show that HE-MSR-COM improves the image quality by 23.95% and 10.6% in two datasets, respectively, compared with HE, contrast-limited adaptive histogram equalization (CLAHE), MSR, and gamma correction (GC). [ABSTRACT FROM AUTHOR]

The DC microgrid does not need to consider frequency when accessing distributed energy, but the distributed energy access port does not have inertia and damping characteristics, so there are problems of voltage instability and power fluctuation. In this paper, the bidirectional DC–DC converter is the main object; based on the virtual synchronous generator (VSG) control strategy, the inertia regulation is added to adjust the bus voltage dynamically. In addition, a balancing strategy is proposed to ensure the balanced distribution of the state of charge (SOC) and power for multiple batteries. Finally, a simulink is built to prove the viability and availability of the VSG control strategy. [ABSTRACT FROM AUTHOR]

This paper studies the sliding mode control method for coupled delayed fractional reaction-diffusion Cohen–Grossberg neural networks on a directed non-strongly connected topology. A novel fractional integral sliding mode surface and the corresponding control law are designed to realize global Mittag-Leffler synchronization. The sufficient conditions for synchronization and reachability of the sliding mode surface are derived via the hierarchical method and the Lyapunov method. Finally, simulations are provided to verify our theoretical findings. [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]

For networked control systems, it is known that various communication parameters in the channel will pose some fundamental limitations on output tracking control (OTC) performance. In this study, we mainly discuss the limitations resulting from model uncertainties, involving channel and plant. Through using the bivariate stochastic process to model packet loss, and the assumption that channel noise is additive white Gaussian noise (AWGN), two explicit expressions of output tracking performance limitations are derived with the single-degree-of-freedom (SDOF) and two-degree-of-freedom (TDOF) control structure, which shows that the performance of OTC is closely related to the inherent characteristics of the plant, as well as the packet loss rate and power spectral density (PSD) of AWGN. Finally, by considering an illustrative example, the simulation results are verified and analyzed to ensure the effectiveness of treatment methods and results. [ABSTRACT FROM AUTHOR]

In this brief, the bipartite consensus problem of linear multi-agent systems with a dynamic event-triggered protocol is studied. A distributed controller with a cooperative-competitive mechanism and estimated states is first designed, and a dynamic event-triggered mechanism proposed in which the triggering threshold is dynamically updated by the designed auxiliary equation. Under this control strategy, the systems only need the states of the agent and neighboring agents at the triggering instants. At the same time, the estimator is considered to reduce the states deviation of multi-agent systems between adjacent triggering instants. Moreover, bipartite consensus can be achieved without Zeno behavior. Finally, the feasibility of the proposed method is illustrated in a unicycle model. [ABSTRACT FROM AUTHOR]

This paper focuses on the ℋ ∞ synchronization issue for fuzzy neural networks via a dynamic event-triggered sliding mode control scheme. In order to relieve the congestion phenomenon in the communication channel, a dynamic event-triggered mechanism is introduced into the sliding mode control design, in which an internal dynamical variable is adopted to fit the event-triggered condition suitably. Moreover, some results with less conservatism are obtained by considering the asynchronous premise variable problem. Then, sufficient criteria are established through the Lyapunov stability theory, which can guarantee that the sliding mode dynamics is asymptotically stable with a given ℋ ∞ performance. In this case, a dynamic event-triggered sliding mode control law is constructed to drive the trajectories of the fuzzy neural networks onto the designed sliding surface. Finally, the effectiveness and superiority of the presented method is verified by an illustrative example. [ABSTRACT FROM AUTHOR]

The finite-time bounded problem for stochastic nonlinear singular systems is discussed in this paper. Firstly, the state observer independent of external disturbances and Brownian motions is designed. Next, the sliding mode function is constructed, which can not only ensure that the system is the finite-time bounded stability, but also its H ∞ performance can be satisfied. The criteria for the finite-time bounded stability and H ∞ finite-time bounded stability of the given system are obtained by Lyapunov function and linear matrix inequalities. Combined with the designed controller, the finite-time stability of the sliding mode function is guaranteed. Finally, the practicability of the control scheme designed is verified by two examples. [ABSTRACT FROM AUTHOR]

This paper is devoted to investigating the impact of the recurrence of rumors and individual behaviors and control strategies related to rumor spreading in online social networks. To do this, a novel susceptible-hesitating-infected-latent-recovered (SHILR) rumor propagation model in heterogeneous networks is presented. Firstly, based on the relevant mean-field equations of the model, the threshold value is examined to demonstrate the existence and stability of rumor-free/spreading equilibrium with the help of the algebraic method. Secondly, the global stabilities of the equilibria are analyzed through applying Lyapunov stability theory and LaSalle's invariance principle. Next, the optimal control is proposed by taking advantage of Pontryagin's maximum principle for reducing the number of infected individuals with minimum cost. Moreover, some numerical examples are carried out to test the theoretical results. Finally, combined with practice, a model application is presented. [ABSTRACT FROM AUTHOR]

The output tracking control problem is investigated in this article. First, a new tradeoff performance index is presented for single-input–multioutput (SIMO) systems. Based on the frequency-domain method, the tracking performance limitations under time delay, packet loss, and channel noise effects are derived. We use a bivariate stochastic process to model the packet loss, and assume that channel noise is additive white Gaussian noise (AWGN). Two explicit expressions of the best tradeoff performance are given with the single-degree-of-freedom (SDOF) and two-degree-of-freedom (TDOF) control structures. It is shown that the tracking control performance has a close relation with the intrinsic characteristic of the plant, as well as the time delay, packet-dropouts rate, and power spectral density of AWGN. We also demonstrate that compared with the SDOF control structure, the TDOF control structure can improve the systems’ attainable performance. A simulation example is finally discussed to validate the conclusions. [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]

In this paper, we employ an efficient numerical method to solve transport equations with given boundary and initial conditions. By the weighted-orthogonal Chebyshev polynomials, we design the corresponding basis functions for spatial variables, which guarantee the stiff matrix is sparse, for the spectral collocation methods. Combining with direct algebraic algorithms for the sparse discretized formula, we solve the equivalent scheme to get the numerical solutions with high accuracy. This collocation methods can be used to solve other kinds of models with limited computational costs, especially for the nonlinear partial differential equations. Some numerical results are listed to illustrate the high accuracy of this numerical method. [ABSTRACT FROM AUTHOR]

This paper investigates the stability of power systems with load frequency control considering time delays (constant and time-varying delays). A new criterion for ensuring the stability of the system is proposed on the basis of Lyapunov stability theory and a further strengthened inequality. Finally, taking a single-area load frequency control scheme with the proportional-integral controller as an example, according to the stability criterion obtained, the relationship between the maximum allowable delay and the gain of proportional-integral controller is discussed. Besides, in case studies, the effectiveness of our method is also demonstrated. [ABSTRACT FROM AUTHOR]

Animals often exhibit dramatically behavioral plasticity depending on their internal physiological state, yet little is known about the underlying molecular mechanisms. The migratory locust, Locusta migratoria, provides an excellent model for addressing these questions because of their famous phase polyphenism involving remarkably behavioral plasticity between gregarious and solitarious phases. Here, we report that a major insect hormone, juvenile hormone, is involved in the regulation of this behavioral plasticity related to phase change by influencing the expression levels of olfactory-related genes in the migratory locust. We found that the treatment of juvenile hormone analog, methoprene, can significantly shift the olfactory responses of gregarious nymphs from attraction to repulsion to the volatiles released by gregarious nymphs. In contrast, the repulsion behavior of solitarious nymphs significantly decreased when they were treated with precocene or injected with double-stranded RNA of JHAMT, a juvenile hormone acid O-methyltransferase. Further, JH receptor Met or JH-response gene Kr-h1 knockdown phenocopied the JH-deprivation effects on olfactory behavior. RNA-seq analysis identified 122 differentially expressed genes in antennae after methoprene application on gregarious nymphs. Interestingly, several olfactory-related genes were especially enriched, including takeout (TO) and chemosensory protein (CSP) which have key roles in behavioral phase change of locusts. Furthermore, methoprene application and Met or Kr-h1 knockdown resulted in simultaneous changes of both TO1 and CSP3 expression to reverse pattern, which mediated the transition between repulsion and attraction responses to gregarious volatiles. Our results suggest the regulatory roles of a pleiotropic hormone in locust behavioral plasticity through modulating gene expression in the peripheral olfactory system. Author summary: A behavioral change from shy solitarious individuals to highly social gregarious individuals is critical to the formation of disastrous swarms of locusts. However, the underlying molecular mechanism of behavioral plasticity regulated by hormones is still largely unknown. Here, we investigated the effect of juvenile hormone (JH) on the behavioral transition in fourth-instar gregarious and solitarious locusts. We found that JH induced the behavioral shift of the gregarious locust from attraction to repulsion to the volatiles of gregarious locusts. The solitarious locust significantly decreased repulsion behavior after deprivation of JH by precocene or knockdown of JHAMT, a key enzyme to synthesize JH. JH application on gregarious locusts caused significant expression alteration of genes, especially the olfactory genes TO and CSP in the antennae. We further demonstrated that the JH signaling pathway suppressed aggregation behavior in gregarious locusts by increasing TO1 expression and decreasing CSP3 expression at the same time. Our results suggested that internal physiological factors can directly modulate periphery olfactory system to produce behavioral plasticity. [ABSTRACT FROM AUTHOR]

This paper deals with the problem for synchronization of a nonlinear time delayed complex spatio-temporal network (CSN), modelled by semi-linear parabolic partial differential-difference equations. A boundary controller relying to distributed measurement is designed. Multiple time-invariant delays are firstly considered. By employing Lyapunov's direct method and Wirtingers inequality, synchronization criteria of the CSN are presented in terms of LMIs. And then, multiple time-varying delays are respectively considered using the boundary controller and synchronization criteria are obtained. Finally, an example illustrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on the problem of simultaneous fault detection and antisaturated control for an inverted pendulum control system. The system input is the acting control voltage that generates the force on the cart. However, the acting control voltage is obviously limited by the voltage amplitude. This means that the actuator of the constructed system model is saturated. Hence, the detector/controller unit produces two signals: the detection and antisaturated control. In this process, the effects of disturbances and noises on detection and control purposes need to be suppressed. Finally, two simulation examples verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This study mainly investigates finite‐time multi‐switching synchronisation of multiple uncertain complex chaotic systems with network transmission mode. Both the unknown parameters and disturbances are considered. By establishing the desired multi‐switching rules, the definition of finite‐time hybrid synchronisation for multi‐systems is first given. Then, sliding mode control approach is used to design the synchronisation controllers, which guarantee that any states of each drive system can synchronise the expected states of every response system in finite time. Simultaneously, the adaptive laws effectively estimate the unknown parameters and the unknown constants of disturbances. Finally, simulation example and analysis display the correctness and effectiveness of all innovations. [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]

This paper concerns the problem of robust H∞ sliding mode control for a class of singular stochastic nonlinear systems. Integral sliding mode control is developed to deal with this problem. Based on the integral sliding surface of the design and linear matrix inequality, a sufficient condition which guarantees the sliding mode dynamics is asymptotically mean square admissible and has a prescribed H∞ performance for a class of singular stochastic nonlinear systems is proposed. Furthermore, a sliding mode control law is synthesized such that the singular stochastic nonlinear system can be driven to the sliding surface in finite time. Finally, a numerical example is proposed to illustrate the effectiveness of the given 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]

Two kinds of finite-time complex function synchronization for multiple complex-variable chaotic systems are investigated. Both the transmission mode and combination mode are respectively considered. By considering complex functions as the scaling factors, the definitions of the two different synchronization mechanisms are established, and the appropriate schemes are proposed to guarantee the finite-time stability of all error systems. Furthermore, two verifiable criteria are derived to synchronize multi-systems. Finally, detailed simulation analysis is provided to validate the effectiveness of all innovations. [ABSTRACT FROM AUTHOR]

In this brief, a class of robust output tracking problems for delayed Boolean control networks is considered under pinning control. First, we give the algebraic representation for such networks, and then a criterion is derived from one-step robust reachability. Next, a constructive program is presented to design feedback pinning controllers. With the use of these controllers, output tracking is achievable. Further, an algorithm and a procedure are given to identify time-optimal pinning controllers. Finally, an example is used to illustrate the advantages and innovation of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the almost periodic dynamical behaviors are considered for delayed complex-valued neural networks with discontinuous activation functions. We decomposed complex-valued to real and imaginary parts, and set an equivalent discontinuous right-hand equation. Depended on the differential inclusions theory, diagonal dominant principle, non-smooth analysis theory and generalized Lyapunov function, sufficient criteria are obtained for the existence uniqueness and global stability of almost periodic solution of the equivalent delayed differential system. Especially, we derive a series of results on the equivalent neural networks with discontinuous activations and periodic coefficients or constant coefficients, respectively. Finally, we give one numerical example to demonstrate the effectiveness of the derived theoretical results. [ABSTRACT FROM AUTHOR]

The study, by using aperiodically intermittent pinning control, is to synchronize switched delayed complex networks with unstable subsystems. Matrix ω-measure and mode-dependent average dwell time method are used to achieve globally exponential synchronization for such system. By designing the useful switching rule and control scheme, we obtain the novel synchronization criteria, which improve the conventional results. Finally, simulation analysis demonstrates the advantages of proposed innovations. [ABSTRACT FROM AUTHOR]

This paper mainly investigates finite-time synchronization of multiple different-order chaotic systems. Two kinds of different network synchronization modes are considered here, and the definitions of finite-time synchronization errors are given for such systems by constructing the proper vectors mapping functions. On the basis of finite-time control idea, the synchronization schemes are developed to ensure the asymptotical stability of two classes of different error systems in finite-time. Afterward, two numerical examples are calculated and simulated to illustrate the effectiveness and feasibility of proposed strategies. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of exponential stability and stabilization for a class of delayed distributed parameter systems, which is modeled by partial integro-differential equations (PIDEs). By employing the vector-valued Wirtinger's inequality, the sufficient condition of exponential stability of the PIDE system with a given decay rate is investigated. The condition is presented by linear matrix inequality (LMIs). After that, we develop a spatial proportional-integral-derivative state-feedback controller that ensures the exponential stabilization of the PIDE system in terms of LMIs. Finally, numerical examples are presented to verify the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

Chemical communication plays an important role in density-dependent phase change in locusts. However, the volatile components and emission patterns of the migratory locust, Locusta migratoria, are largely unknown. In this study, we identified the chemical compositions and emission dynamics of locust volatiles from the body and feces and associated them with developmental stages, sexes and phase changes. The migratory locust shares a number of volatile components with the desert locust ( Schistocerca gregaria), but the emission dynamics of the two locust species are significantly different. The body odors of the gregarious nymphs in the migratory locust consisted of phenylacetonitrile (PAN), benzaldehyde, guaiacol, phenol, aliphatic acids and 2,3-butanediol, and PAN was the dominant volatile. Volatiles from the fecal pellets of the nymphs primarily consist of guaiacol and phenol. Principal component analysis (PCA) showed significant differences in the volatile profiles between gregarious and solitary locusts. PAN and 4-vinylanisole concentrations were significantly higher in gregarious individuals than in solitary locusts. Gregarious mature males released significantly higher amounts of PAN and 4-vinylanisole during adulthood than mature females and immature adults of both sexes. Furthermore, PAN and 4-vinylanisole were completely lost in gregarious nymphs during the solitarization process, but were obtained by solitary nymphs during gregarization. The amounts of benzaldehyde, guaiacol and phenol only unidirectionally decreased from solitary to crowded treatment. Aliphatic aldehydes (C7 to C10), which were previously reported as locust volatiles, are now identified as environmental contaminants. Therefore, our results illustrate the precise odor profiles of migratory locusts during developmental stages, sexes and phase change. However, the function and role of PAN and other aromatic compounds during phase transition need further investigation. [ABSTRACT FROM AUTHOR]

This paper mainly addressed the stability analysis and the estimation of domain of attraction for the endemic equilibrium of a class of susceptible-exposed-infected-quarantine epidemic models. Firstly, we discuss the global stability of the disease-free equilibrium and the local stability of the endemic equilibrium in the feasible region D of the epidemic model, respectively. Secondly, we use a geometric approach to investigate the global stability of the endemic equilibrium in a positive invariant region $$D_s(\subset D)$$ . Furthermore, we estimates the domain of attraction for the endemic equilibrium via sum of squares optimization method, and obtain the optimal estimation by solving an semidefinite programming problem with sum of squares polynomial constraints. Finally, numerical simulation is examined to demonstrate the feasibility and effectiveness of the research results. [ABSTRACT FROM AUTHOR]