Synchronization Problem Research Articles

Nonlinear RISE based integral reinforcement learning algorithms for perturbed Bilateral Teleoperators with variable time delay

In view of unknown Bilateral Teleoperators, the simultaneous satisfaction of not only synchronous control problem between two sides, but also optimal control performance under time-varying delays and external disturbance is a difficult task. Initially, in order to address this challenge, we proposed two control approaches including On-Policy and Off-Policy strategies after employing the sliding variable to reduce the order of dynamic model. Additionally, since the development of the unification between synchronous control problem and optimal control performance, it requires the consideration of discount factor addition to guarantee the bound of the infinite horizon cost function. In order to handle the dynamic uncertainties and the exponential cost function, by fully considering data collection technique in model-free On-Policy and Off-Policy strategies, Reinforcement Learning control schemes are proposed to guarantee the optimality effectiveness. Consequently, the Robust Integral of the Sign of the Error term is integrated into two proposed optimal control frames to improve the synchronous control performance and estimation capability of dynamic uncertainties. Moreover, the convergence of control policies and synchronous control problem of two proposed control frames are rigorously analyzed by Lyapunov stability theory. Finally, simulation results and the comparisons with the existing controller demonstrate the effectiveness of two proposed control frameworks.

Synchronising a stereoscopic surgical video stream using specular reflection.

A stereoscopic surgical video stream consists of left-right image pairs provided by a stereo endoscope. While the surgical display shows these image pairs synchronised, most capture cards cause de-synchronisation. This means that the paired left and right images may not correspond once used in downstream tasks such as stereo depth computation. The stereo synchronisation problem is to recover the corresponding left-right images. This is particularly challenging in the surgical setting, owing to the moist tissues, rapid camera motion, quasi-staticity and real-time processing requirement. Existing methods exploit image cues from the diffuse reflection component and are defeated by the above challenges. We propose to exploit the specular reflection. Specifically, we propose a powerful left-right comparison score (LRCS) using the specular highlights commonly occurring on moist tissues. We detect the highlights using a neural network, characterise them with invariant descriptors, match them, and use the number of matches to form the proposed LRCS. We perform evaluation against 147 existing LRCS in 44 challenging robotic partial nephrectomy and robotic-assisted hepatic resection video sequences with simulated and real de-synchronisation. The proposed LRCS outperforms, with an average and maximum offsets of 0.055 and 1 frames and 94.1±3.6% successfully synchronised frames. In contrast, the best existing LRCS achieves an average and maximum offsets of 0.3 and 3 frames and 81.2±6.4% successfully synchronised frames. The use of specular reflection brings a tremendous boost to the real-time surgical stereo synchronisation problem.

Control and synchronisation of an extended hyperchaotic system based on robust switching control

This paper introduces a new class of hyperchaotic systems developed based on Chen's hyperchaotic system. The hyperchaotic nature of the developed system is proven through the calculation of the positive Lyapunov exponent and simulation. A robust feedback control method is then introduced to stabilise the system. To enhance the security of telecommunication channels for information exchange, a switching structure comprising extended hyperchaotic systems is presented. The synchronisation problem of the proposed structure is addressed using a robust switched linear control method. The simulation results show the effectiveness of the proposed controller in guaranteeing system stability and solving the synchronisation problem thus increasing security in telecommunication networks.

The role of local bounds on neighborhoods in the network for scale‐free state synchronization of multi‐agent systems

AbstractThis article provides necessary and sufficient conditions for the existence of solutions to the state synchronization problem of homogeneous multi‐agent systems (MAS) via scale‐free linear dynamic non‐collaborative protocol in both continuous and discrete time. These conditions guarantee for which class of MAS, one can achieve scale‐free state synchronization. We investigate protocol design with and without utilizing local bounds on the neighborhood of agents. The results shows that the availability of local bounds on neighborhoods plays a key role.

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays

This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. Secondly, linear and adaptive feedback controllers with sign function are designed respectively. Furthermore, through Lyapunov direct method, DTFO inequality technique and Razumikhin theorem, some sufficiency criteria are obtained to ensure that the system in this article can achieve LPS. At last, the significance of the theoretical part of this paper is verified through numerical simulation.

Admissible and dissipative synchronisation of fractional order singular systems with time delay using event-triggered feedback control

The purpose of this work is to study the admissible and dissipative synchronisation of fractional order singular systems with time delay. The key goal is to use as few network resources as possible while retaining the desired closed-loop performance. An event-triggered control method is used to accomplish this. The Lyapunov function method, linear matrix inequality approach, and mathematical techniques are used to develop new synchronisation criteria that assure the synchronisation error system is Mittag–Leffler stable. Because fractional order differential equations have memory characteristics, which are very different from ordinary differential equations, leading to difficulties in preventing Zeno behaviour related to the event-triggered mechanism of fractional order systems, especially of delayed fractional order singular systems. To solve this issue, we propose a new theoretical framework and a new condition to preclude Zeno behaviours. This derived conditions use inequality techniques and take advantage of a number of fundamental aspects of fractional order calculus. Furthermore, the dissipative synchronous problem of delayed fractional order singular systems is also solved for the first time using the suggested stable criterion in conjunction with some auxiliary characteristics of fractional calculus. Two numerical examples are provided to demonstrate the usefulness of the proposed strategy.

The global Mittag-Leffler synchronization problem of Caputo fractional-order inertial memristive neural networks with time-varying delays

The global Mittag-Leffler synchronization problem of Caputo fractional-order inertial memristive neural networks with time-varying delays

Neural network-based distributed intelligent supervisory control for multi-agent systems with unknown input powers

In this paper, a synchronisation problem is studied for a class of nonlinear leader-following systems. Based on adaptive control with some algebra lemmas, we propose a distributed control scheme. This scheme ensures each follower to asymptotically synchronise with the leader. Compared with the existing works where system input powers are assumed one, the input powers considered in this paper are unknown but larger than one. Based on Graph theory, Lyapunov theory and radial basis function (RBF) networks, we design a distributed adaptive supervisory control method. It is proven that the consensus among the leader and followers are achieved and all the signals including tracking errors asymptotically converge to a small neighbourhood of the origin. Finally, simulation results are displayed to demonstrate the effectiveness of control scheme.

Phase-locking-free all-optical matching system for 100 Gbaud QPSK optical signal

Photonic firewall is a monitoring protection device that will directly detect and locate optical network attacks at the optical layer, which can effectively ensure the security of optical networks. An all-optical matching system is the core part of photonic firewall, which determines the performance of a photonic firewall, so it is of great significance to research and develop all-optical matching system for high-speed and high-order modulation formats signals. At present, an all-optical matching system for binary modulation formats is relatively mature, but the all-optical matching system for high-order phase modulation format signals is still limited by how to solve the problem of phase synchronization. In this paper, a new all-optical matching system based on self-interference matching is proposed for quadrature phase shift keying (QPSK) optical signal, which avoids the introduction of local target sequence optical signals and phase-locking circuits. The theoretical analysis and simulation verification are conducted for the designed system. The results demonstrate that the system can accurately identify and locate 4-symbol or 8-symbol target sequences in the input QPSK optical signals with 16-symbol and 32-symbol data sequences at a data rate of 100 Gbaud.

A Molecular Communication Perspective on Synchronization of Coupled Microfluidic-Spectroscopy.

A challenge for real-time monitoring of biochemical processes, such as cells, is detection of biologically relevant molecules. This is due to the fact that spectroscopy methods for detection may perturb the cellular environment. One approach to overcome this problem is coupled microfluidic-spectroscopy, where a microfluidic output channel is introduced in order to observe biologically relevant molecules. This approach allows for non-passive spectroscopy methods, such as mass spectrometry, to identify the structure of molecules released by the cell. Due to the non-negligible length of the microfluidic channel, when a sequence of stimuli are applied to a cell it is not straightforward to determine which spectroscopy samples correspond to a given stimulus. In this paper, we propose a solution to this problem by taking a molecular communication (MC) perspective on the coupled microfluidic-spectroscopy system. In particular, assignment of samples to a stimulus is viewed as a synchronization problem. We develop two new algorithms for synchronization in this context and carry out a detailed theoretical and numerical study of their performance. Our results show improvements over maximum-likelihood synchronization algorithms in terms of detection performance when there are uncertainties in the composition of the microfluidic channel.

SE(3) Synchronization by eigenvectors of dual quaternion matrices

Abstract In synchronization problems, the goal is to estimate elements of a group from noisy measurements of their ratios. A popular estimation method for synchronization is the spectral method. It extracts the group elements from eigenvectors of a block matrix formed from the measurements. The eigenvectors must be projected, or ‘rounded’, onto the group. The rounding procedures are constructed ad hoc and increasingly so when applied to synchronization problems over non-compact groups. In this paper, we develop a spectral approach to synchronization over the non-compact group $\mathrm{SE}(3)$, the group of rigid motions of $\mathbb{R}^{3}$. We based our method on embedding $\mathrm{SE}(3)$ into the algebra of dual quaternions, which has deep algebraic connections with the group $\mathrm{SE}(3)$. These connections suggest a natural rounding procedure considerably more straightforward than the current state of the art for spectral $\mathrm{SE}(3)$ synchronization, which uses a matrix embedding of $\mathrm{SE}(3)$. We show by numerical experiments that our approach yields comparable results with the current state of the art in $\mathrm{SE}(3)$ synchronization via the spectral method. Thus, our approach reaps the benefits of the dual quaternion embedding of $\mathrm{SE}(3)$ while yielding estimators of similar quality.

SYNCHRONIZATION PROBLEMS OF SIMULTANEOUS TRANSLATION

Among the many difficulties encountered in simultaneous interpreting - an important feature of multilingual communication in various international contexts - synchronization issues stand out. This article analyzes many synchronization problems and the nature of synchronization problems, their causes, effects, and potential solutions. We highlight the technological, environmental, and cognitive components that create these challenges. We will also discuss modern strategies and methods to reduce the difficulties and problems during synchronization, while improving the accuracy and efficiency of simultaneous interpretation.

Non-fragile projective synchronization of delayed discrete-time neural networks via generalized weighted summation inequality

This paper explores the problem of exponential projective synchronization (EPS) for delayed discrete-time uncertain neural networks (NNs) subject to non-fragile state feedback control. To attain less conservative results, some generalized weighted summation inequalities are proposed, which encompass Jensen-based summation inequality (JBSI) as its special case. By constructing suitable Lyapunov-Krasovskii functional (LKF), sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to ensure the EPS via newly introduced weighted summation inequalities. Finally, numerical examples are provided, supported by simulation results through MATLAB software that ensures the efficiency of the desired theoretical outcomes and the comparative study in terms of maximum allowable upper bound (MAUB) evaluates the effectiveness of the established results by enhancing the feasible region.

Pinning event-triggered sampled-data synchronization of coupled reaction–diffusion neural networks

In this paper, the synchronization problem of coupled reaction–diffusion neural networks (CRDNNs) is considered by using pinning event-triggered sampled-data (PETSD) control method under spatially point measurements. To save the limited transmission channel, a PETSD control mechanism by controlling a small fraction of the nodes is proposed to decrease the update frequency of controller and the unnecessary SD. Then, based on the Lyapunov–Krasovskii functional (LKF) and inequality techniques, sufficient conditions for exponential stability of the synchronization error system presented by linear matrix inequalities (LMIs) can be derived through the designed PETSD controller. Finally, simulation results of one numerical example are presented to demonstrate the effectiveness of the proposed design approach.

Fixed Time Synchronization of Stochastic Takagi–Sugeno Fuzzy Recurrent Neural Networks with Distributed Delay under Feedback and Adaptive Controls

In this paper, the stochastic Takagi–Sugeno fuzzy recurrent neural networks (STSFRNNS) with distributed delay is established based on the Takagi–Sugeno (TS) model and the fixed time synchronization problem is investigated. In order to synchronize the networks, we design two kinds of controllers: a feedback controller and an adaptive controller. Then, we obtain the synchronization criteria in a fixed time by combining the Lyapunov method and the related inequality theory of the stochastic differential equation and calculate the stabilization time for the STSFRNNS. In addition, to verify the authenticity of the theoretical results, we use MATLABR2023A to carry out numerical simulation.

A novel direct method to [formula omitted] synchronization of switching inertial neural networks with mixed time-varying delays

In this paper, the H∞ synchronization problem of switching inertial neural networks with mixed time-varying delays is discussed. A parameterized system solution-based direct analysis method combined with minimum residence time method is proposed to solve the considered problem. The advantage of this method is that no model transformation or construction of Lyapunov–Krasovskii functional is required, thus reducing the complexity of derivation process. In addition, the resulting synchronization conditions composed of some simple scalar inequalities can be easily solved via MATLAB. Finally, the reliability of the theoretical results is illustrated by numerical simulations.

Order sequencing, tote scheduling, and robot routing optimization in multi-tote storage and retrieval autonomous mobile robot systems

This study explores a novel multi-tote storage and retrieval autonomous mobile robot system, where multi-tote autonomous mobile robots transport totes (or ‘SKU bins’) for order picking. We investigate the joint optimisation problem of order sequencing, tote scheduling, and robot routing in a single workstation equipped with the capacity to accommodate multiple order bins and parallel totes. The inbound and outbound streams of SKUs stored in totes are crucial for order picking at the workstation, as they jointly affect the picking performance efficiency through synchronization with the order sequence. To address this synchronization problem, we formulate a Mixed-Integer Linear Programming (MILP) model and propose a two-stage hybrid heuristic combining a variable neighbourhood search (VNS) algorithm and a refinement model. This model further improves the VNS solution with partially fixed SKU inbound stream and problem-tailored inequalities. Our numerical studies highlight the superior performance of the proposed hybrid heuristic, where the VNS solution surpasses the benchmark VNS-Simplified by a significant margin of 14%. The rearrangement process enhances the VNS performance by reducing 33.8% of SKU revisits. We also offer managerial insights, suggesting that the maximum number of order bins and parallel totes, exhibit boundary points where adding capacity yields limited marginal improvements.

Reinforcement learning-based secure synchronization for two-time-scale complex dynamical networks with malicious attacks

This paper studies the secure synchronization problem for two-time-scale complex dynamical networks with unknown dynamics information and malicious attacks. The challenge is that under complex dynamic networks with unknown dynamic information, all system matrices are unknown. To ameliorate this conundrum, we design a reinforcement learning algorithm, conjoined with a full-order processing of singularly perturbed parameters, with the express objective of securing the stability of the synchronization error system within a context devoid of adversarial intrusions. Second, in order to reduce the impact of malicious attacks, a switching function is developed based on feedback gain. Besides, it is proved that the proposed distributed controllers can still guarantee the convergence of the synchronization error system under malicious attacks. Finally, two numerical examples are given to illustrate the applicability and effectiveness of the proposed algorithm.

The Synchronisation and Standardisation of Time (1830-1970): Technological Innovation and Public Policy

Clock-making has represented a fundamental sector for industrialisation, al-lowing a more precise division of labour and developing the competences for au-tomation, which was well understood by Charles Babbage. Besides precision, the problems of synchronisation and standardisation have characterised the creation of the uniform time dimension. This paper proposes the history of these processes with a glance at their protagonists. Scientific progress, technological innovation, institutions and cultural frames co-evolved assuring a favourable frame to indus-trialisation. That was possible thanks to a synergy between astronomers and clock-makers as well as between inventors and railways. Even when exact time was made a public good, access to it was quite demanding in technological terms. The history of railways let us understand how reliability and trust have been the crucial variables in the making of the industrialised society. Conventions and the passion of technicians with a faith in progress have been more relevant than the often disorienting action of governments or the uncertainty of market competition.

Optimal Design of Data Acquisition System for Fault Diagnosis of Hydraulic Machinery

Abstract Fault diagnosis of hydraulic machinery has high requirements on the synchronization of monitoring data and the anti-interference of monitoring equipment. The performance and data quality of the existing operation monitoring equipment of the unit cannot meet the requirements. At the same time, due to the variety of sensors and the different wiring methods of different types of sensors, the preparation work such as wiring of data acquisition equipment in the test is complicated. This paper analyzes the application requirements of fault diagnosis data and the problems existing in the conventional data collection process. A data collection solution specified for diagnosis of hydraulic machinery, which better solves the problem of data synchronization, is designed. The new designed system has high sampling accuracy and anti-interference characteristics, as well as the advantages of strong capability and simple equipment deployment. The proposed system has been applied in multiple power stations, pumping stations and pump test platforms. The relevant functions have been effectively verified.