Adaptive Coupling Research Articles

Influence of adaptive coupling points on coalition formation in multi-energy systems

The share and variants of coupling points (CPs) between different energy carrier networks (such as the gas or power grids) are increasing, which results in the necessity of the analysis of so-called multi-energy systems (MES). One approach is to consider the MES as a graph network, in which coupling points are modeled as edges with energy efficiency as weight. On such a network, local coalitions can be formed using multi-agent systems leading to a dynamic graph partitioning, which can be a prerequisite for the efficient decentralized system operation. However, the graph can not be considered static, as the energy units representing CPs can shut down, leading to network decoupling and affecting graph partitions. This paper aims to evaluate the effect of network adaptivity on the dynamics of an exemplary coalition formation approach from a complex network point of view using a case study of a benchmark power network extended to an MES. This study shows: first, the feasibility of complex network modeling of MES as a cyber-physical system; second, how the coalition formation system behaves, how the coupling points impact this system, and how these impact metrics relate to the CP node attributes.

Dynamical origin of the explosive synchronization with partial adaptive coupling

Explosive synchronization underlying many abrupt dynamical phenomena has attracted a great deal of attention in various fields. Here, we untangle the dynamical origin of the explosive synchronization in a system of coupled phase oscillators, incorporating partial adaptation encoded by feedback between the coupling and the global rhythm of the population. We mathematically argue that there exists no a critical adaptive fraction for the synchronization transition converting from the second to first order. Explosive synchronization, which is much easier to achieve than previously deemed, takes place as long as the adaptive fraction is nonzero. In particular, we uncover that an atypical scaling of the order parameter near criticality, manifesting the metastable state in the hysteresis region, is responsible for the emergence of explosive synchronization. Our work thus provides a profound insight into the dynamical nature of the abrupt transitions induced by the adaptation, a dynamical phenomenon of continuous interest and subject to intense investigation.

Fully Distributed Observer Design for Mobile Targets

In this paper, a sensor network is used to implement the distributed observer design problem for a linear time-invariant mobile target system with constant or time-varying velocity. Each sensor can only access a part of the output information of the target. Two types of interacting dynamics are endowed to each sensor, one is a consensus-based algorithm for the state estimation using the local measurements, while the other is a leader-following flocking-like algorithm such that the mobile sensors can avoid collision, maintain communication, and track the target. By adopting adaptive coupling gains on the consensus-based term in the state estimation algorithm, a fully distributed observer which is independent of the communication topology associated with the sensor network is constructed. Finally, numerical simulations are presented to illustrate the effectiveness of the proposed theoretical results.

Two-scale modeling of particle crack initiation and propagation in particle-reinforced composites by using microscale analysis based on Voronoi cell finite element model

In this study, a two-scale finite element model has been developed for the elastic analysis of composite materials. The coarse finite element mesh was assumed for the macroscale analysis, while Voronoi cell finite element model (VCFEM) was used for the microscale analysis of heterogeneous domains. The adaptive coupling between the two scales in non-critical and critical regions was accomplished through the master–slave nodes method. Two scale elements were connected together through the use of shared nodes and the order of the edge displacement interpolation. A new extended VCFEM was proposed to simulate particle damage generation, and a remeshing algorithm was constructed to simulate particle crack generation and propagation in particle-reinforced composites. For crack propagation analysis, four new combined Voronoi elements were developed and analyzed at the microscale. The obtained results for the stresses, stress intensity factors, and crack path were compared with those calculated using the commercial calculation software Abaqus. The two sets of results are in very good agreement, confirming the accuracy of the proposed method used for determining the stress concentrations and also for coarse-mesh discretization.

Interplay of inertia and adaptive couplings in the emergent dynamics of Kuramoto ensemble

We study the emergent dynamics of Kuramoto oscillators under the interplay between inertia and adaptive couplings. For the phase dynamics, we use the inertial Kuramoto model with time-dependent mutual coupling strengths. For the constant and uniform coupling strength, the inertial Kuramoto model can exhibit the slow relaxation dynamics toward phase-locked state under suitable conditions on system parameters and initial data. To model the time-evolution of mutual coupling strengths, we employ two types of coupling functions, namely “Hebbian coupling” and “anti-Hebbian coupling”. With these modeling spirit, the resulting coupled dynamics for the phase and mutual coupling strength becomes the coupled second-order and first-order systems of ordinary differential equations. For the proposed coupled system, we provide several sufficient frameworks for phase and frequency synchronization in terms of system parameters and initial data for Hebbian and anti-Hebbian coupling functions.

A fast adaptive PD-FEM coupling model for predicting cohesive crack growth

In this study, nonlocal theory of peridynamic (PD) is coupled with finite element method (FEM) to simulate cohesive crack growth in quasi-brittle materials. The adaptive dynamic relaxation method is adopted to implement quasi-static loading conditions. The advantage of peridynamic method in the modeling of crack propagation is taken into consideration to be coupled with that of finite elements which is computationally less expensive and covers various boundary value problems. In this novel method, the whole domain of the problem is initially dominated by FEM solver with coarse mesh grids. Coupling process is then introduced to those regions which have critical conditions according to damage criterion. The capability of the proposed coupling method in the modeling of cohesive crack growth in quasi-brittle materials is demonstrated. In comparison to other conventional PD-FEM coupling methods, the computational cost of the proposed method is considerably improved and total running time of the solution is significantly attenuated. The validity of the method is confirmed through comparing the results with experimental ones.

Pattern Selection in Multilayer Network with Adaptive Coupling

Feed-forward effect strongly modulates collective behavior of a multiple-layer neuron network and usually facilitates synchronization as signals are propagated to deep layers. However, a full synchronization of neuron system corresponds to functional disorder. In this work, we focus on a network containing two layers as the simplest model for multiple layers to investigate pattern selection during interaction between two layers. We first confirm that the chimera state emerges in layer 1 and it also induces chimera in layer 2 when the feed-forward effect is strong enough. A cluster is discovered as a transient state which separates full synchronization and chimera state and occupy a narrow region. Second, both feed-forward and back-forward effects are considered and we discover chimera states in both layers 1 and 2 under the same parameter for a large range of parameters selection. Finally, we introduce adaptive dynamics into inter-layer rather than intra-layer couplings. Under this circumstance, chimera state can still be induced and coupling matrix will be self-organized under suitable phase parameter to guarantee chimera formation. Indeed, chimera, cluster and synchronization can propagate from one layer to another in a regular multiple network for a corresponding parameter selection. More importantly, adaptive coupling is proved to control pattern selection of neuron firing in a network and this plays a key role in encoding scheme.

Synchronization dynamics of phase oscillators with generic adaptive coupling

Adaptive coupling schemes among interacting elements are ubiquitous in real systems ranging from physics and chemistry to neuroscience and have attracted much attention in recent years. Here, we extend the Kuramoto model by considering a particular adaptive scheme in a system of globally coupled oscillators. The homogeneous coupling is correlated with the global coherence of the population that is weighted by the generic nonlinear feedback function of the amplitude of the order parameter. The studied model is analytically tractable that generalizes the theory of Kuramoto for synchronization transition. We develop a mean-field theory by establishing the self-consistent equation describing the stationary dynamics in the thermodynamic limit. Importantly, the Landau damping effect, which turns out to be far more generic, is revealed in the framework of the linear stability analysis of the resonant pole theory. Furthermore, the relaxation rate of the order parameter in the subcritical region is obtained from a universal formula. Our study can deepen the understanding of synchronization transitions and other related collective dynamics in networked oscillators with adaptive interaction schemes.

Numerical Simulation Research on Rotating Band Dynamic Engraving Process of CTA Artillery

In order to study the mechanical mechanism of the dynamic engraving process of the CTA band, the simulation model of the engraving process is established considering the friction and contact characteristics between the interfaces. The adaptive FEM-SPH coupling algorithm is used to obtain the variation law of the temperature and stress distribution of the band, the attitude of the projectile, and the dynamic engraving resistance through numerical calculation. The results show that the band undergoes plastic flow during engraving, and the surface temperature of the band is close to the melting point temperature of the material during the adiabatic engraving. The engraving process presents obvious segmented characteristics, and the initial engraving speed has an important influence on the spatial projectile attitude. The variation of dynamic engraving resistance is quite different from that of the quasi-static model, and the resistance has two ‘rising-decreasing’ processes.

Observer-Based Dynamic Event-Triggered Adaptive Control of Distributed Networked Systems With Application to Ground Vehicles

In this paper, a distributed observer-based event-based practical consensus control for networked systems subject to adaptive nonlinear couplings is investigated. Considering that the node's state is not always measurable and the finite communication bandwidth exists in engineering systems, two distributed adaptive event-triggered control protocols subject to nonlinear couplings are proposed under observer-based dynamic output feedback. Then, distributed dynamic event-triggered control policies corresponding to two above mentioned adaptive controllers are proposed, respectively. The proposed nonlinear coupled event-triggered control schemes not only overcome continuous communication among nodes, but also relax the requirement of relying on global information for achieving a distributed practical consensus. Finally, the theoretical analysis is verified through a team of practical networked ground vehicles implemented thorough Matlab/Similink and Robot Operating Systems (ROS) environment.

Passivity and Control for Multiweighted and Directed Fractional-Order Network Systems

We conduct the study of passivity and control for multiweighted and directed fractional-order network systems (MDFONSs) in this article. A new concept of fractional-order passivity (FOP) is defined, which also contains the integer-order passivity. In the literature of multiweighted networks, many papers usually study its passivity only from the viewpoint of outer coupling matrices (OMs), which are also assumed to be connected and undirected. In this article, we add the viewpoint of inner coupling matrices (IMs), and the OMs can be directed and not connected, which can greatly improve the existing results. By means of decomposing IMs into their main diagonal matrices and residual matrices, we obtain that if the weighted combination of multiple OMs for each dimension is strongly connected, then FOP can be realized. Of course, the above results also hold for diagonal IMs, which is commonly addressed in previous works. Moreover, synchronization, adaptive coupling strengths and pinning control are also discussed. Besides, FOP and control rules for multiweighted and directed fractional-order reaction-diffusion network systems (MDFORDNSs) are derived by applying this strategy. Numerical examples are ultimately employed to examine the effectiveness of these gained results.

Fully Distributed Dynamic Edge-Event-Triggered Current Sharing Control Strategy for Multibus DC Microgrids With Power Coupling

Although the current sharing control of dc microgrids has been widely studied, the high communication bandwidth and global communication network structure information demands hander the renewable energy consumption. Thus, this article proposes a fully distributed dynamic edge-event-triggered current sharing control strategy for multibus dc microgrids with power coupling. First, the system model with power coupling is built, which is further switched to the linear heterogeneous multiagent systems with unknown disturbance. It is an indispensable preprocessing for controller design. Furthermore, the fully distributed current sharing control strategy is proposed through adaptive coupling weights. Note that the global communication network structure information demand is eliminated. Moreover, the fully distributed dynamic edge-event-triggered mechanism is proposed to reduce communication bandwidth. Compared with the previous dynamic event-triggered mechanisms applied into dc microgrids, the continuous communication between neighboring agents is avoided, and controller updating frequency is reduced. Finally, the simulation and experimental results verify the proposed control performance.

Robust and reusable self-organized locomotion of legged robots under adaptive physical and neural communications.

Animals such as cattle can achieve versatile and elegant behaviors through automatic sensorimotor coordination. Their self-organized movements convey an impression of adaptability, robustness, and motor memory. However, the adaptive mechanisms underlying such natural abilities of these animals have not been completely realized in artificial legged systems. Hence, we propose adaptive neural control that can mimic these abilities through adaptive physical and neural communications. The control algorithm consists of distributed local central pattern generator (CPG)-based neural circuits for generating basic leg movements, an adaptive sensory feedback mechanism for generating self-organized phase relationships among the local CPG circuits, and an adaptive neural coupling mechanism for transferring and storing the formed phase relationships (a gait pattern) into the neural structure. The adaptive neural control was evaluated in experiments using a quadruped robot. The adaptive neural control enabled the robot to 1) rapidly and automatically form its gait (i.e., self-organized locomotion) within a few seconds, 2) memorize the gait for later recovery, and 3) robustly walk, even when a sensory feedback malfunction occurs. It also enabled maneuverability, with the robot being able to change its walking speed and direction. Moreover, implementing adaptive physical and neural communications provided an opportunity for understanding the mechanism of motor memory formation. Overall, this study demonstrates that the integration of the two forms of communications through adaptive neural control is a powerful way to achieve robust and reusable self-organized locomotion in legged robots.

Numerical Study on the Breaking Process of the Seafloor Massive Sulfide Based on the FEM-SPH Adaptive Coupling Algorithm

The research on seafloor massive sulfide (SMS) started relatively late, and the results on its breaking process are few. However, the breaking process contains evaluation indexes of safe, efficient and low-disturbance mining, so it is necessary to study the breaking process of seafloor massive sulfide. At the same time, the finite element method is used in most existing researches, and the system will automatically delete the failure element from the system during the simulation of rock-breaking, resulting in the inability to accurately obtain the chip state in the breaking process. In addition, SPH meshless method has unique advantages in dealing with large deformations of rock-breaking, but it has the problems of difficultly in boundary processing and serious computational time. In view of this, a hybrid discretization method of finite element method and smooth particle hydrodynamics (SPH) is proposed in this paper. On this basis, numerical simulation of a single-pick cutting seafloor massive sulfide based on the FEM-SPH adaptive coupling algorithm is carried out. Through the research in this paper, the regularity of the fragmentation process of polymetallic sulfides is obtained: firstly, the breaking process of seafloor massive sulfide experiences four stages: cutting-in of the pick, evolution of the high-stress zone, formation of the dense core, and the chips’ splash. Secondly, the three-dimensional forces on the pick change in fluctuation in the cutting process. Thirdly, the stress wave propagation is unbalanced and biased in the cutting process. Fourthly, the chips’ splash mainly has three directions: jet flow towards the opposite direction of the cutter cutting, spluttering perpendicular to the cutting surface of the pick, and sliding along the cutting surface. Finally, the chip mass is positively correlated with the cutting time. In this paper, a simulation framework for rock-breaking is proposed, and its advantages have been effectively verified.

A coupling approach of the isogeometric–meshfree method and peridynamics for static and dynamic crack propagation

A coupling approach of the isogeometric–meshfree method and the peridynamic method is developed for static and dynamic crack propagation. The coupling approach exhibits advantages in the flexibility of modeling cracks and the exactness of geometry representation. The isogeometric–meshfree method, which adopts the moving least-squares approximations to establish the equivalence between meshfree shape functions and isogeometric basis functions, is capable of obtaining the exact geometry. The isogeometric–meshfree nodes located on the geometry can be directly coupled with peridynamic points by the balanced force principle, which is straightforward and effective. With this approach, the boundary conditions can be enforced directly using the isogeometric–meshfree method, and the surface effects of peridynamics are effectively eliminated. Moreover, the present approach is flexible in switching the isogeometric–meshfree nodes to peridynamic points and achieving adaptive coupling with the same convergence rate as the one for the isogeometric–meshfree method, which is higher than the one for the original peridynamic method. The dual-horizon peridynamic method is adopted for non-uniform discretization. Based on the exact geometry representation, the coupling approach is further extended to crack problems with contact loading. Several representative examples are presented to validate the effectiveness of the present approach in solving static/dynamic crack problems and studying fractures caused by contact.

Explosive synchronization in phase oscillator populations with attractive and repulsive adaptive interactions

The attractive and repulsive adaptive coupling schemes among dynamical agents are ubiquitous in systems ranging from physics, biology to neuroscience, which have attracted increasing interest and ample attention during recent years. Here, we extend the classical Kuramoto model to the coupling with mixed signs by considering a particular adaptive scheme in a system of globally coupled phase oscillators. The time-varying coupling weight between each pair of oscillators is correlated with the local coherence that involves according to a nonlinear differential equation. The studied model is capable of capturing the essential properties of the explosive synchronization induced by the adaptive interactions. We carry out extensive simulations to explore the collective dynamics in different perspectives. Remarkably, we reveal that the occurrence of the abrupt transitions of the macroscopic overall weights, as well as the emergence of the correlations between the microscopic structure features (including degrees and frequency dissasortativity) and local dynamics trigger the explosive synchronization, which manifests the suppression rule for the formation of small synchronized clusters. Furthermore, we provide an analytical treatment for the reduced system that allows us to grasp the underlying mechanism of the observed phenomena. Our study can deepen the understanding of the explosive synchronization transitions and other related abrupt dynamic phenomena occurring in networked oscillators with generic adaptive schemes.

Cyclops States in Repulsive Kuramoto Networks: The Role of Higher-Order Coupling.

Repulsive oscillator networks can exhibit multiple cooperative rhythms, including chimera and cluster splay states. Yet, understanding which rhythm prevails remains challenging. Here, we address this fundamental question in the context of Kuramoto-Sakaguchi networks of rotators with higher-order Fourier modes in the coupling. Through analysis and numerics, we show that three-cluster splay states with two distinct coherent clusters and a solitary oscillator are the prevalent rhythms in networks with an odd number of units. We denote such tripod patterns cyclops states with the solitary oscillator reminiscent of the Cyclops' eye. As their mythological counterparts, the cyclops states are giants that dominate the system's phase space in weakly repulsive networks with first-order coupling. Astonishingly, the addition of the second or third harmonics to the Kuramoto coupling function makes the cyclops states global attractors practically across the full range of coupling's repulsion. Beyond the Kuramoto oscillators, we show that this effect is robustly present in networks of canonical theta neurons with adaptive coupling. At a more general level, our results suggest clues for finding dominant rhythms in repulsive physical and biological networks.

Consensus of Fixed and Adaptive Coupled Multi-Agent Systems with Communication Delays

This paper aims to solve the consensus problem of three different types of multi-agent systems under fixed communication delay. For these three different types of multi-agent systems, three new control protocols are constructed to solve the consensus issue of multi-agent systems with coupling weights, which is rarely considered in other related articles. For fixed coupled multi-agent systems, a new control strategy is designed by Lyapunov theory, matrix theory, and the inequality method to ensure the consensus of multi-agent systems. An adaptive coupling weight updating scheme is proposed for adaptive coupling multi-agent systems to achieve the consensus state of the multi-agent systems. Finally, experimental results show the effectiveness of the proposed three different algorithms.

The approach of hybrid adaptive coupling synchronization among N Lorenz systems and its application in secure communication for multi‐unmanned aerial vehicle formation

SummaryIn this paper, it is proposed that a hybrid global adaptive coupling synchronization scheme among Lorenz chaotic dynamical nodes to realize the secure communication system between base station and multi‐unmanned aerial vehicle (UAV) formation. The specific method is that the feedback drive–response synchronization is utilized for first two nodes of base station and the leader of multi‐UAV formation, and the nodes of all UAVs are coupled by unidirectional adaptive coupling synchronization according to a directed link in ad hoc network of multi‐UAV formation. It is demonstrated that the asymptotic stability of the proposed hybrid adaptive coupled synchronization by constructing the Lyapunov function. In this way, the encrypted information formed by plaintext information masked into the chaotic sequence generated by the chaotic dynamical node of base station; meanwhile, it is fed back into the base station node as the drive system. On the other hand, encrypted information is forwarded to the leader node as the response system for decryption. The feedback driver–response synchronization is used to realize secure communication between the base station and the leader of multi‐UAV formation. Meanwhile, secure communication among its leader and followers is achieved through the unidirectional adaptive coupling synchronization in the network. This strategy ensures the multi‐UAV formation decrypting encrypted information synchronously and effectively improves the security, consistency, and overall performance of their commands.

A Multitimescale Kalman Filter-Based Estimator of Li-Ion Battery Parameters Including Adaptive Coupling of State-of-Charge and Capacity Estimation

This article deals with coupled, state, and parameter estimation for lithium-ion batteries described by an equivalent circuit model, including polarization dynamics. Since the model parameters depend on the battery state-of-charge (SoC) and temperature operating point, as well as on the battery state-of-health, all states and parameters need to be estimated simultaneously for an accurate overall estimation during the battery lifetime. The proposed estimation algorithm is structured in two timescales: 1) slow-scale, sigma-point Kalman filter (KF)-based estimation of battery capacity and 2) fast-scale, dual-extended KF-based estimation of SoC and model parameters. A particular emphasis is on the adaptive parameterization of SoC and capacity estimators, which provides robust coupling between two timescales and ensures favorable convergence and robust capacity tracking in conditions of SoC and model parameters’ estimation errors. In support of estimation accuracy analysis, an algebraic observability analysis of impedance parameters is conducted. Also, by introducing an observability index calculated in each simulation timestep, a comparison of degrees of observability of different impedance parameter subsets is allowed for. The proposed estimation algorithm is verified both by simulation and experimentally for an electric scooter Li-NMC battery pack.