Synchronization Problem Research Articles

The Dilemma Of Indonesia’s Coal Policy In 2020-2060: A Modality Of State Revenue

<em>Coal commodity management policies in Indonesia are closely related to efforts to reduce carbon emissions and increase carbon sequestration. This has the potential to create regulatory synchronization problems because it relates to sectoral challenges from the relevant ministries and/or agencies. To describe the synchronization problem, this research uses a normative juridical method with a statute approach and a conceptual approach. The results of this study are that there are three ministries that are directly or indirectly related to coal management, namely the Ministry of Energy and Mineral Resources, the Ministry of Environment and Forestry, and the Ministry of Finance. The conclusion is that although the 2005-2025 national development target has been announced by the Government, particularly regarding the NZE2060 target, it turns out that the implementation of the regulations in the three ministries has experienced predicaments that have resulted in a dilemma of synchronizing the national climate policy. However, short-term policies implicitly indicate the modality of state revenue as a priority</em>

Aperiodically synchronization of multi-links delayed complex networks with semi-Markov jump and their numerical simulations to single-link robot arms

This paper investigates the pth moment exponential synchronization problem of multi-links stochastic delayed complex networks with semi-Markov jump via aperiodically intermittent control. Combining random disturbances, time-varying delay and semi-Markov jump with multi-links systems, our work is more relevant than previous work. Based on Lyapunov method and graph theory, a novel inequality for disposing of the problem of pth exponential synchronization is established under the aperiodically intermittent control and some sufficient criteria are derived. The theoretical results supply a new perspective showing the synchronization criterion and the topological structure of multi-links systems related closely. Furthermore, the value of our results is exhibited by applying them to the single-link robot arms in engineering. Eventually, a numerical simulation is provided to demonstrate the validity of our results.

Exponential synchronization of quaternion-valued memristor-based Cohen-Grossberg neural networks with time-varying delays: norm method.

In this paper, the exponential synchronization of quaternion-valued memristor-based Cohen-Grossberg neural networks with time-varying delays is discussed. By using the differential inclusion theory and the set-valued map theory, the discontinuous quaternion-valued memristor-based Cohen-Grossberg neural networks are transformed into an uncertain system with interval parameters. A novel controller is designed to achieve the control goal. With some inequality techniques, several criteria of exponential synchronization for quaternion-valued memristor-based Cohen-Grossberg neural networks are given. Different from the existing results using decomposition techniques, a direct analytical approach is used to study the synchronization problem by introducing an improved one-norm method. Moreover, the activation function is less restricted and the Lyapunov analysis process is simpler. Finally, a numerical simulation is given to prove the validity of the main results.

Event-triggered hybrid impulsive control for synchronization of fractional-order multilayer signed networks under cyber attacks

In this paper, we consider the exponential bipartite synchronization (EBS) problem of fractional-order multilayer signed networks with time-varying delays (FO-MSNT) under random cyber attacks. In contrast to the existing literature, the proposed hybrid event-triggered controller combines the advantages of feedback controller and impulsive controller, and the event-triggered condition is constructed by applying the network topology and the Lyapunov function of the subsystem, rather than the state function of the subsystem. Based on the Lyapunov–Razumikhin method and the graph theory, some sufficient conditions for achieving EBS of FO-MSNT under cyber attacks which are related to the topology of networks, the event-triggered parameters, the order of fractional derivative and the signal sent by the enemy are obtained. Furthermore, fractional-order coupled Chua’s circuits model and fractional-order power systems built on MSNT are established and the EBS issues under cyber attacks are analyzed. Numerical examples and simulations are provided to show the validity of our theories.

Tradeoff analysis between time cost and energy cost for fixed-time synchronization of discontinuous neural networks

This article focuses on the tradeoff analysis between time and energy costs for fixed-time synchronization (FXTS) of discontinuous neural networks (DNNs) with time-varying delays and mismatched parameters. First, a more comprehensive lemma is systematically established to study fixed-time stability, which is less conservative than those in most current results. Besides, theoretical proof has proven that the upper bounds of the settling time (ST) in this article are more accurate compared to existing results. Second, on the grounds of the new fixed-time stability lemma, fixed-time synchronization problem for discontinuous neural networks with time-varying delays and mismatched parameters is explored, and sufficient conditions for fixed-time synchronization are obtained. Further, the upper bounds of energy cost during the synchronization process are estimated. Third, in order to achieve a balance between time cost and energy cost, the genetic algorithm is utilized to find the satisfactory control parameter. Finally, a numerical example is provided to verify the theoretical analysis’s correctness and the control mechanism’s feasibility.

Coopetition-dependent controller design for bipartite synchronization of cooperation–competition delayed memristive neural networks

In this paper, the bipartite synchronization problem for cooperation–competition delayed memristive neural networks (CCDMNNs) is addressed via designing a coopetition-dependent controller. Based on the coordinate transformation technique, an easy-to-analyze error system is constructed in the presence of cooperation–competition interactions. Two control strategies are proposed respectively to realize bipartite synchronization. First of all, a coopetition-dependent controller that can eliminate the impact of cooperation–competition interactions as well as the time-varying state-dependent memristive connection weights is designed. In combination with inequality techniques, the Lyapunov theory and the interval matrix method, an LMI-form criterion is established to ensure the bipartite synchronization of CCDMNNs. Moreover, an adaptive controller that can automatically adjusts the control parameters to achieve appropriate control gains is proposed to further improve the control performance. Finally, a numerical example is given to verify the correctness and superiority of the proposed control schemes.

Non-fragile exponential synchronisation of stochastic neural networks via aperiodic intermittent impulsive control

This study aims to address the non-fragile exponential synchronisation problem of stochastic neural networks (SNNs). To cut down unnecessary control costs, a novel aperiodic intermittent-based impulsive control (APIIC) is designed in this investigation. Besides, the randomly occurring gain fluctuation (ROGF) is considered in APIIC, which satisfies certain Bernoulli distributed white noise sequences. By exploiting the Lyapunov approach and the average dwell-time technique, some sufficient criteria are derived in terms of linear matrix inequalities, which ensure that APIIC can achieve exponential synchronisation of SNNs with and without ROGF. More intriguingly, a technical definition of aperiodic window-based average impulsive interval is developed to cut back the conservativeness of these results. At last, the effectiveness of our explored results is confirmed by several numerical examples.

Fixed‐time synchronization and energy cost estimation of delayed coupled neural networks

AbstractThis article concentrates on the fixed‐time synchronization (FTS) and energy cost (EC) problems of delayed coupled neural networks (NNs). A switching controller is proposed and some sufficient conditions are advanced to ensure FTS of delayed coupled NNs based on the comparison theorem. Following that, the required EC is estimated during the control process. The main results of FTS and EC for considered NNs are obtained based on the Lyapunov functions in the sense of vector 1‐norm, 2‐norm, and ‐norm, respectively. Under the same controller parameters, this article shows that the minimum estimation of settling time and EC are sometimes not in one norm sense. Finally, numerical examples are given to show the effectiveness of theoretical results.

Delay-independent control for synchronization of memristor-based BAM neural networks with parameter perturbation and strong mismatch via finite-time technology

This paper mainly studies the synchronization problem of memristor-based bidirectional associative memory neural networks (MBAMNNs) via finite-time technology. Different from the existing neural network dynamic models, the given model in this paper is focused on the impact of parameter perturbation and strong mismatch, where strong mismatch includes parameter mismatch and time-varying delay mismatch. These characteristics can make the model be closer to the actual situation. A delay-independent feedback control scheme, which can stabilize the error system within finite-time regardless of whether the past state is known or not, is designed. It is worth noting that the constant is replaced by a function with the exponential term in the delay-independent controller, which can save the control cost to a certain extent. Based on the integral inequality technique, some sufficient conditions for MBAMNNs to converge to the equilibrium point within finite-time are provided. The validity and correctness of the theoretical results are finally confirmed by numerical simulation.

Employment of Synchronized Chaotic SHA256 Random Number Generators along with their Application in the Field of Image Encryption

Background: Current work is associated with the deployment of synchronized chaotic Secure Hash Algorithm (SHA256) random number generators along with their application in image encryption. Methods: This study aimed to design a perfect communication system to encrypt and decrypt the images via image processing. We introduced a new sliding mode scheme for master-slave fourdimensional (4D) Lorenz-Stenflo systems to deal with the synchronization problem. Then, a new synchronized dynamic secure hash algorithm (SHA-256) was implemented to generate the dynamic random numbers. Results: An image encryption and decryption mechanism was implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values. Here, the master systems were used for encryption, and the slave systems were responsible for the decryption mechanism. The complete design of this paper was implemented in a Python environment. Conclusion: The demonstration of simulation results includes the state responses, strange attractors, and synchronization error responses of master-slave chaotic systems with appropriate switching functions and control input. conclusion: An image encryption and decryption mechanism has been implemented by using synchronized chaotic master-slave systems corresponding to the generated hash values other: The complete design of this paper has been implemented on python environment

Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control

In this paper, we investigate the exponential synchronization problem for multi-link and multi-delayed inertial neural networks with Markov jump (MMDINNMJ) using an aperiodically intermittent adaptive control strategy. Different from most research on inertial neural networks, we take multi-link, multi-delay and Markov jump into account. The obstacle caused by the coexistence of Markov jump and multi-delay is avoided by using the delayed integral method while considering the exponential synchronization of MMDINNMJ. Additionally, under graph theory, Lyapunov stability theory and the developed control scheme, some novel sufficient conditions for synchronization at exponential rate in pth (p>0) moment of underlying networks are determined, which are strongly related to multi-link topological structure, time delay, and Markov jump. Finally, two examples are given to demonstrate the viability of the theoretical conclusions.

Simple solution of DC-offset rejection based phase-locked loop for single-phase grid-connected converters

Distributed Generators (DG) systems based on Renewable Energy Sources (RES) such as hydro, wind, and solar power plants have been spread widely due to their lower cost and the advanced capability of connecting them with the grid. The power generated from the DG must be shaped to be interfaced with the grid employing power electronics converters. The grid-connected power electronics converters must be synchronized with the grid (i.e., the same fundamental component of the grid frequency, phase, amplitude, and sequence). Synchronization techniques are employed to achieve accurate and fast grid synchronization between the converter and the grid. The existence of (DC-offset) in the input of Phase Locked Loop (PLL) caused synchronization problems as it causes oscillations in the estimated fundamental grid phase, frequency, and amplitude. In addition, the closed-loop system stability can be affected. This work proposes a simple technique for grid synchronization based on PLL with a phase angle correction. The proposed method was developed using Transfer Delay (TD) and Delay Signal Cancelation (DSC) operators; then, the small single model and stability analysis was employed. Several scenarios were developed to compare the proposed method with previous methods using MATLAB/Simulink tool. The scenarios involve introducing phase jumps, DC offsets, and amplitude changes to the grid voltage. Additionally, the grid frequency was also changed. The results show that the proposed PLL can solved the DC-offset problem using any delay time and fully synchronized with the grid. Moreover, the proposed PLL has the fastest dynamic response and shortest synchronization time over the other methods from literature.

Synchronization analysis of delayed quaternion-valued memristor-based neural networks by a direct analytical approach

<abstract><p>This issue discusses the asymptotic synchronization and the exponential synchronization for memristor-based quaternion-valued neural networks under the time-varying delays. Some criteria for synchronization of the memristor-based quaternion-valued neural networks are given by exploiting the set-valued theory, the differential inclusion theory, some analytic techniques, as well as constructing novel controllers, It is worth noting that the synchronization problem about the memristor-based quaternion-valued neural networks were studied by the direct analysis method in this paper. Finally, the main theoretical results were verified by numerical simulations.</p></abstract>

Optimal Task and Motion Planning and Execution for Multiagent Systems in Dynamic Environments.

Combining symbolic and geometric reasoning in multiagent systems is a challenging task that involves planning, scheduling, and synchronization problems. Existing works overlooked the variability of task duration and geometric feasibility intrinsic to these systems because of the interaction between agents and the environment. We propose a combined task and motion planning approach to optimize the sequencing, assignment, and execution of tasks under temporal and spatial variability. The framework relies on decoupling tasks and actions, where an action is one possible geometric realization of a symbolic task. At the task level, timeline-based planning deals with temporal constraints, duration variability, and synergic assignment of tasks. At the action level, online motion planning plans for the actual movements dealing with environmental changes. We demonstrate the approach's effectiveness in a collaborative manufacturing scenario, in which a robotic arm and a human worker shall assemble a mosaic in the shortest time possible. Compared with existing works, our approach applies to a broader range of applications and reduces the execution time of the process.

Prefixed-Time Local Intermittent Sampling Synchronization of Stochastic Multicoupling Delay Reaction-Diffusion Dynamic Networks.

This article focuses on the problem of prefixed-time synchronization for stochastic multicoupled delay dynamic networks with reaction-diffusion terms and discontinuous activation by means of local intermittent sampling control. Notably, unlike the existing common fixed-time synchronization, this article puts forward a new synchronization concept, prefixed-time synchronization, based on the fact that stochastic noise and discontinuous activation can be seen everywhere in practical engineering, which can effectively perfect and improve the existing works. Specifically, a local intermittent in the time domain and point sampling control strategy in the spatial domain is proposed instead of a simple single intermittent control approach, which greatly reduces the control cost. In addition, by some effective means, including the famous Young's inequality, Jensen's inequality, and Hölder's inequality, we obtain two different synchronization criteria of the networks without delay and with multicoupling delays and deeply reveal the quantitative relationship among control period, point sampling length, and network scale. Finally, a numerical example is given to verify the effectiveness of the developed method and the practicability by Chua's circuit model.

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.

Finite-Time Synchronization of Complex Dynamical Networks With Input Saturation.

In the framework of input saturation, this article studies the problem of finite-time synchronization (FTS) of a class of complex dynamical networks. By designing different classes of saturated controllers, two types of FTS criteria, including leader-follower synchronization and leaderless synchronization, are presented, respectively. A potential relationship between the saturation structure, the settling time, and the domain of attraction is established, which is crucial to achieve FTS. It shows that the saturation structure not only affects the estimation of domain of attraction but also possibly changes the settling time for FTS. Two numerical examples are presented to illustrate the effectiveness of the proposed results.

Mittag-Leffler projective synchronization of uncertain fractional-order fuzzy complex valued neural networks with distributed and time-varying delays

<p>To study the Mittag-Leffler projective synchronization (MLPS) problem of fractional-order fuzzy neural networks (FOFNNs), in this work we introduced the FOFNNs model. On this basis, we discussed the MLPS of uncertain fractional-order fuzzy complex valued neural networks (FOFCVNNs) with distributed and time-varying delays. Utilizing Banach contraction mapping principle, we proved the existence and uniqueness of the model solution. Moreover, employing the construction of a new hybrid controller, an adaptive hybrid controller, and the fractional-order Razumikhin theorem, algebraic criteria was obtained for implementing MLPS. The algebraic inequality criterion obtained in this article improves and extends the previously published results on MLPS, making it easy to prove and greatly reducing the computational complexity. Finally, different Caputo derivatives of different orders were given, and four numerical examples were provided to fully verify the accuracy of the modified criterion.</p>

Heterogeneous multi-drone and helicopter routing problem for reconnaissance

Helicopters and drones are widely used in military and post-disaster reconnaissance. But less attention has been paid to collaborative reconnaissance between the two, especially when drones can be launched and retrieved multiple times. We propose a synchronous routing problem of helicopter and heterogeneous multi-drone for reconnaissance, which is a new variant of the orienteering problem (OP), where the drones can visit multiple mission nodes and can reconnoiter the retrieval nodes in a single trip, with the goal of maximizing the information collected. The problem is formulated as a mixed integer linear programming (MILP) model, and then an adaptive simulated annealing algorithm (A-SA) is designed to solve the problem. Specifically, a universal high-efficiency heuristics solution evaluation method based on segment sorting is proposed. The time complexity of this method is O(n). The numerical experiments illustrate the accuracy and efficiency of the algorithm. The results also show that allowing the drones to conduct reconnaissance on the retrieval nodes can positively impact the solution.

Finite-Time Output Synchronization of Multiple Weighted Reaction-Diffusion Neural Networks With Adaptive Output Couplings.

This article mainly considers the output synchronization (OS) problem of multiple weighted and adaptive output coupled reaction-diffusion neural networks (RDNNs) without and with coupling delays in finite time. Without coupling delays, an adaptive control law and an output feedback controller are, respectively, proposed to ensure that the multiple weighted and output coupled RDNNs are output synchronized and output synchronized in finite time. With coupling delays, an adaptive coupling weights control scheme and a novel feedback controller are put forward to make the multiple weighted RDNNs with output couplings achieve OS in finite time. Moreover, the finite-time OS is considered in the presence of external disturbances. By the Lyapunov approach, several finite-time OS and OS criteria are given. Finally, two simulation examples are presented to justify the effectiveness of the proposed adaptive control laws and controllers.