Synchronization Problem Research Articles

Master–Slave Finite-Time Synchronization of Chaotic Fractional-Order Neural Networks under Hybrid Sampled-Data Control: An LMI Approach

In this paper, a hybrid controller with a sampled data control is investigated to achieve finite-time master–slave synchronization of delayed fractional-order neural networks (DFONNs). A Lyapunov-Krasovskii functional is constructed to obtain the sufficient conditions that incorporate delay information. For the first time, the asymptotic stability of the error system is guaranteed in a finite-time using the inequality technique and a sampled-data hybrid controller. The obtained conditions are expressed via linear matrix inequality. Notably, the proposed approach outperforms existing methods, demonstrating improved results in a comparative analysis. An explicit formula is utilized to calculate the settling time, which is significantly influenced by the fractional order 0<β≤1. The superior performance of the proposed control method is evident, showcasing its effectiveness through numerical simulations and addressing the synchronization problem in DFONNs.

Intermittent hold control for exponential synchronization of fractional-order delayed complex networks with its application

The paper focuses on synchronization problems of a type of fractional-order complex systems with delays. First, a general exponential stability theorem is achieved by utilizing function of complex variable method and fractional-order calculus, which can handle a type of multiple delayed complex systems. Then, a novel intermittent-hold control is designed, which can reduce the information transmission by flexibly adjusting the control interval. Next, through the proposed theorem and controller, exponential synchronization results can be obtained by constructing simple Lyapunov functional. Meanwhile, the control gains can be calculated by linear matrix inequality. Finally, two simulations are given to show the effectiveness of the proposed results, and some comparisons with different control times and holding times verify the flexibility of control time selection.

High-Accuracy Clock Synchronization in Low-Power Wireless sEMG Sensors

Wireless surface electromyography (sEMG) sensors are very practical in that they can be worn freely, but the radio link between them and the receiver might cause unpredictable latencies that hinder the accurate synchronization of time between multiple sensors, which is an important aspect to study, e.g., the correlation between signals sampled at different sites. Moreover, to minimize power consumption, it can be useful to design a sensor with multiple clock domains so that each subsystem only runs at the minimum frequency for correct operation, thus saving energy. This paper presents the design, implementation, and test results of an sEMG sensor that uses Bluetooth Low Energy (BLE) communication and operates in three different clock domains to save power. In particular, this work focuses on the synchronization problem that arises from these design choices. It was solved through a detailed study of the timings experimentally observed over the BLE connection, and through the use of a dual-stage filtering mechanism to remove timestamp measurement noise. Time synchronization through three different clock domains (receiver, microcontroller, and ADC) was thus achieved, with a resulting total jitter of just 47 µs RMS for a 1.25 ms sampling period, while the dedicated ADC clock domain saved between 10% to 50% of power, depending on the selected data rate.

Event-triggered synchronisation of unknown heterogeneous coupled harmonic oscillators

This note concentrates on event-triggered synchronisation problem of unknown heterogeneous coupled harmonic oscillators (CHOs). We develop an event-triggered synchronisation algorithm that does not rely on any continuous information transmission among oscillators and global topology information. For this end, we first design an observer to estimate unknown system parameter for each oscillator. Second, each oscillator uses information received from its neighbours to estimate the frequency of leader oscillator and its neighbours' states. Based on estimated frequencies and states, we design an adaptive synchronisation algorithm for CHOs to solve synchronisation problem. We prove that CHOs, under proposed synchronisation algorithm, reach state synchronisation, and there is no Zeno behaviour. In the end, a simulation is presented to check proposed synchronisation algorithm.

Fixed-time Synchronization of Caputo/Conformable Fractional-Order Inertial Cohen-Grossberg Neural Networks via Event-triggered One/Two-phase Hybrid Impulsive Control

This paper is concerned with the fixed-time synchronization (FXS) problems of Caputo/conformable fractional-order inertial Cohen-Grossberg neural networks (FOICGNNs) by one/two-phase hybrid impulsive control (HIC) through event-triggered update strategies. By utilizing the properties of fractional calculus, several novel inequalities regarding the fixed-time convergence of hybrid impulsive systems (HIS) are obtained. We especially discuss and compare the cases of Caputo and conformable fractional order to gain deep insight into fractional calculus. By applying the Lyapunov stability theory, two hybrid controllers, which consist of event-triggered continuous controllers and impulsive controllers, are designed to realize the FXS of FOICGNNs. It’s worth pointing out that, we unprecedentedly study and compare the differences of the one-phase HIC and two-phase HIC, where a novel nonlinear impulsive controller is proposed and designed to obtain fixed-time convergence in the impulsive control phase. In addition, the exclusion of Zeno behavior is proved for the designed event-triggered strategy. Finally, several numerical examples are provided to illustrate the feasibility of the proposed control approach and the correctness of the theoretical results.

Finite-Time Synchronization of Fractional-Order Complex-Valued Multi-Layer Network via Adaptive Quantized Control Under Deceptive Attacks

This article investigates the problem of finite-time synchronization of fractional-order complex-valued random multi-layer networks without decomposing them into two real-valued systems. Firstly, by promoting real-valued signum functions, sign functions on the complex-valued domain are introduced. Simultaneously, quantization functions in the complex-valued domain are also introduced, and several related formulas for sign functions and quantization functions in complex-valued domain are established. Under the framework of the given sign function and quantization function, an adaptive quantized control scheme with or without deception attacks is designed. According to the finite-time theorem, Lyapunov function, and graph theory methods, some sufficient criteria for realizing finite-time synchronization in complex-valued fractional-order multi-layer networks have been obtained. Furthermore, the setting time of finite-time synchronization is effectively evaluated. Eventually, the reliability of our results and the practicality of control strategies are verified through numerical examples.

Synchronization in Public Transportation: A Review of Challenges and Techniques

Performing synchronization in public transport is one of the most challenging tasks that transport managers perform when organizing the processes of passenger servicing. Many variables characterizing existing public transport lines should be considered in the final timetable; in addition, the complexity of the transportation system, the variability in transport demand, and the stochasticity of the servicing process both in time and space have a significant influence on the result of synchronization. The synchronization problem in real-world applications does not have an exact solution, so in practice, a variety of techniques were developed to achieve a rational solution in a reasonable time. In our paper, we classify existing approaches to solving the problem of public transport synchronization, describe the essence of the most promising methods, and study their popularity based on the most recent scientific publications. As the result of our research, we show the most promising directions for the future development of synchronization methods and their application in public transportation.

Edges’ Riemannian energy analysis for synchronization of multi-agent nonlinear systems over undirected weighted graphs

In this note we investigate the problem of global exponential synchronization of multi-agent systems described by non-linear input affine dynamics. We consider the case of networks described by undirected connected graphs possibly without leader. We present a set of sufficient conditions based on a Riemannian metric approach in order to design a state-feedback distributed control law. Then, we study the convergence properties of the overall network. By exploiting the properties of the edge Laplacian we construct a Lyapunov function that allows to conclude global exponential synchronization of the overall network.

Secure synchronization control for complex dynamic networks with event-triggered communication strategy under multi-channel denial-of-service attacks.

This article addresses the secure synchronization problem for complex dynamical networks (CDNs) with observer-based event-triggered communication strategy (ETCS) under multi-channel denial-of-service attacks (MCDSAs). Due to external environmental interference, the observers are designed to accurately estimate the state of the network systems. Meanwhile, the impact of cyber attacks on system security is considered. Differing from other studies, MCDSAs in this paper are considered, which present the interference of malicious attacks on the communication topology, observers and controllers. Based on the characteristics of cyber attacks, the model for CDNs with nonperiodic switching topology is established, and the observer-based intermittent control is proposed to achieve synchronization of CDNs. To decrease the network communication frequency and reduce the risk of cyber attacks, a new ETCS depending on estimate states is designed. Then, using Lyapunov stability theory, several synchronization conditions depending on the status parameters of MCDSAs are deduced, which may estimate the allowable ranges for the duration and frequency of MCDSAs. From these theoretical results, it can be observed that the destructive power of network attacks increases exponentially with the increase of attack duration. Finally, from simulation experiments, the availability of the designed controller and communication strategy is verified, which can ensure the synchronization for CDNs with MCDSAs.

Event-triggered synchronization control for neural networks against DoS attacks

&lt;p&gt;This paper studied the event-triggered synchronization problem for time-delay neural networks under DoS attacks. A novel event-triggered scheme based on switching between periodic sampling and a continuous event-triggered scheme was proposed, which not only cuts down the number of data transmissions but also offsets cyberattacks. By choosing a suitable piecewise Lyapunov-Krasovskii functional and using several free-weighting matrices, sufficient conditions were established to ensure the exponential stability of the synchronization error system in the occurrence of DoS attacks. Furthermore, a co-design method was provided to acquire the desired non-fragile output-feedback control gain and event-triggering parameter. Finally, a numerical example was given to illustrate the usefulness of the proposed approach.&lt;/p&gt;

Novel adaptive boundary control for synchronization of fractional fuzzy Cohen-Grossberg BAM neural networks with reaction-diffusion and time-varying delay

ABSTRACT The boundary synchronization problem for a class of fractional fuzzy Cohen-Grossberg BAM neural networks (FFCGBAMNNs) with reaction-diffusion and time-varying delay is studied. Novel adaptive boundary controllers, Neumann boundary conditions, and fuzzy feedback MIN and MAX templates of nonlinear dynamic fuzzy modeling are employed. Based on the adaptive boundary controllers with fractional adaptive updated laws and the appropriate Lyapunov-Krasovskii functional (LKF), new sufficient criteria are derived to ensure that the drive-response FFCGBAMNNs achieve asymptotic and finite-time boundary synchronization in terms of the linear matrix inequality (LMI). Based on these sufficient criteria, the effects of adaptive boundary controller on asymptotic and finite-time stability are analyzed. Finally, numerical simulations are presented to illustrate the feasibility of the theoretical results.

Synchronisation of complex nonlinear dynamical networks with coupling delays via dual hybrid-triggered control design

The synchronisation problem for a class of complex nonlinear dynamical networks (CNDNs) that are subject to time-varying coupling delays and nonlinearities is explored in this work. This is accomplished by designing a dual hybrid-triggered communication technique based on the dynamic output feedback controller which is the main intent of this study. In contrast to the existing hybrid-triggered mechanism, a dual hybrid-triggered technique is being employed with the utilisation of outputs of considered CNDNs and the dynamic output feedback controller. To be precise, with an aim to effectively lower the network transmission rate in both the sensor-to-controller and controller-to-actuator channels, the triggering mechanism is implemented to both the outputs. Later, the Lyapunov–Krasovskii functional is utilised to establish the stability criterion and the necessary conditions for ensuring the synchronisation of chosen CNDNs are derived in terms of linear matrix inequalities. Eventually, two numerical examples, including the aircraft model have been rendered to reveal the potency of acquired theoretical results.

Efficient Solution of Sequences of Parametrized Lyapunov Equations With Applications

ABSTRACTSequences of parametrized Lyapunov equations can be encountered in many application settings. Moreover, solutions of such equations are often intermediate steps of an overall procedure whose main goal is the computation of , where denotes the solution of a Lyapunov equation and is a given matrix. We are interested in addressing problems where the parameter dependency of the coefficient matrix is encoded as a low‐rank modification to a seed, fixed matrix. We propose two novel numerical procedures that fully exploit such a common structure. The first one builds upon the Sherman‐Morrison‐Woodbury (SMW) formula and recycling Krylov techniques, and it is well‐suited for small dimensional problems as it makes use of dense numerical linear algebra tools. The second algorithm can instead address large‐scale problems by relying on state‐of‐the‐art projection techniques based on the extended Krylov subspace. We test the new algorithms on several problems arising in the study of damped vibrational systems and the analyses of output synchronization problems for multi‐agent systems. Our results show that the algorithms we propose are superior to state‐of‐the‐art techniques as they are able to remarkably speed up the computation of accurate solutions.

Globally Exponential Synchronization of Delayed Complex Dynamic Networks With Average Impulsive Delay‐Gain

ABSTRACTIn this article, we investigate globally exponential synchronization problems in delayed complex dynamic networks (DCDNs) characterized by both time‐varying impulsive delay and gain (TIDG). Our research is grounded on the Halanay inequality, which serves as the keystone of our analysis. Adopting the method of average impulsive delay‐gain (AIDG), we formulate criteria for globally exponential synchronization dependent on the overall impulsive disturbances. Our criteria reveal the negative effect of AIDG on synchronization, which hinders the synchronization process. Additionally, we refine the concept of average impulsive gain to enhance its applicability. Furthermore, our results demonstrate that even in the simultaneous presence of desynchronizing and synchronizing impulses, along with time‐varying impulsive delays, DCDNs are able to maintain the original synchronization under appropriate conditions, irrespective of whether the average impulsive interval is finite or not. Finally, we validate our theoretical findings by applying them to network examples.

Variable Gain Impulsive Synchronization for Discrete-Time Delayed Neural Networks and Its Application in Digital Secure Communication.

This article revisits the problems of impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks (DDNNs) in the presence of disturbance in the input channel. A new Lyapunov approach based on double Lyapunov functionals is introduced for analyzing exponential input-to-state stability (EISS) of discrete impulsive delayed systems. In the framework of double Lyapunov functionals, a pair of timer-dependent Lyapunov functionals are constructed for impulsive DDNNs. The pair of Lyapunov functionals can introduce more degrees of freedom that not only can be exploited to reduce the conservatism of the previous methods, but also make it possible to design variable gain impulsive controllers. New design criteria for impulsive stabilization and impulsive synchronization are derived in terms of linear matrix inequalities. Numerical results show that compared with the constant gain design technique, the proposed variable gain design technique can accept larger impulse intervals and equip the impulsive controllers with a stronger disturbance attenuation ability. Applications to digital signal encryption and image encryption are provided which validate the effectiveness of the theoretical results.

Pinning Synchronization for Stochastic Complex Networks With Randomly Occurring Nonlinearities: Tackling Bit Rate Constraints and Allocations.

In this article, the ultimately bounded synchronization problem is investigated for a class of discrete-time stochastic complex networks under the pinning control strategy. Communication between system nodes and the remote controller is facilitated via wireless networks subject to bit rate constraints. The system model is distinguished by the inclusion of randomly occurring nonlinearities. A coding-decoding transmission mechanism under constrained bit rates is introduced to characterize the digital transmission process. To achieve synchronization of the network nodes with the unforced target node, a pinning controller is specifically devised based on the information from partially selected nodes. Through the application of the stochastic analysis method, a sufficient condition is derived for ensuring the mean-square boundedness of the synchronization error system. In addition, an optimization algorithm is introduced to address bit rate allocation and the design of desired controller gains. Within the presented theoretical framework, the correlation between the mean-square synchronization performance and bit rate allocation is further elucidated. To conclude, a simulation example is provided to substantiate the efficacy of the recommended pinning control approach.

An Adaptive Procedure of Time Synchronization in Unstructured Multi-Hop Wireless Sensor Networks using Butterfly Optimization Algorithm

Abstract Wireless sensor networks (WSNs) play a pivotal role in various applications, ranging from environmental monitoring to defence technology. This paper proposes a novel time synchronization protocol for WSNs inspired by the Butterfly Optimization algorithm. The time synchronization problem is formulated into an optimization problem for heuristic evolutionary algorithms, and the recently reported Butterfly optimization algorithm is used to optimize clock parameters and carry out global network synchronization. A working protocol is proposed for clock synchronization in multi hop WSN. The proposed protocol is evaluated experimentally against the Newton inspired Time Synchronization protocol and the Average Proportional Integral Synchronization protocol. Experimental results showed better performance in terms of synchronization accuracy as compared to the other protocols.

Synchronization of complex dynamical networks with saturated delayed impulsive control.

This paper considers the local exponential synchronization problem for a type of complex dynamical networks (CDNs) with both system delay and coupled delay using saturated delayed impulsive control. Based on the methods of average impulsive interval (AII), average impulsive delay (AID) and average impulsive estimation (AIE), a Razumikhin-type inequality with hybrid delayed impulses (which include delayed impulses and delay-free impulses) is derived. This inequality includes pure delayed impulsive inequalities. By utilizing the constructed inequality and the Lyapunov stability theory, the saturation nonlinearities are treated as the convex hulls, and sufficient synchronization criteria for local exponential synchronization of CDNs are presented in the framework of linear matrix inequalities (LMIs). Moreover, to enlarge the estimation of region of attraction (ROA) and the design of impulsive control gain, a convex optimization problem based on LMIs is formulated. Finally, a numerical example demonstrates the effectiveness of the obtained results.

Development of the parallel and distributed simulation field

This paper documents the origins and development of the parallel and distributed simulation field, especially as it relates to parallel discrete event simulation (PDES) technology. My focus is on the people and ideas that contributed to the creation and evolution of PDES technology over the past five decades. Much of this paper reviews the research conducted in academia and research laboratories that were the driving forces behind the development of PDES technology as well as subsequent efforts in government and industry to bring the technology to modeling and simulation practitioners. The origins of PDES technology lie in a fundamental technical issue called the synchronization problem. This problem is discussed, as well as the two main solution approaches that were created. The development of these approaches and their evolution to form the time management services of the High Level Architecture (HLA) standard are described, as well as the community of researchers and practitioners that formed in establishing this field. Commercialization efforts are discussed followed by a brief discussion of areas requiring further research. The importance of the Society for Modeling and Simulation International (SCS) and its flagship journal, Simulation, in the development of the field are discussed. Throughout this discussion, I provide my personal observations and take away lessons concerning the development of the field.

Accuracy-preassigned fixed-time synchronization of switched inertial neural networks with time-varying distributed, leakage and transmission delays

In this paper, the accuracy-preassigned fixed-time synchronization problem of a class of switched inertial neural networks with time-varying distributed, leakage and transmission delays is studied. To this end, a parameterized system solution-based direct analysis method is proposed for the first time. Unlike existing works, this method sets out from the definition of accuracy-preassigned fixed-time synchronization, and does not require variable substitution for inertial item or the construction of any Lyapunov–Krasovskii functional. This not only simplifies the proof process, but also reduces the computational complexity for solving synchronization conditions. Significantly, this paper introduced the time-varying leakage delay into switched inertial neural networks for the first time. Furthermore, the approach utilized in this manuscript stands apart from all previous techniques for achieving fixed-time synchronization. Finally, the reliability of the theoretical results is verified by numerical simulation.