Connectivity Preservation Research Articles

Distributed formation tracking with connectivity preservation and orientation alignment

This paper investigates the formation tracking problem incorporating connectivity preservation and orientation alignment for multi-agent systems. Consider the body-fixed frame of each agent in the multi-agent system is initialized with different orientations. To achieve formation controller design by relative position in the body-fixed frame, the orientation of the frames should be aligned first. A distributed passive-based orientation controller is proposed to ensure convergence of all body-fixed frames toward a unified desired orientation. Once the frames are aligned, a barrier Lyapunov function (BLF)-based formation tracking controller is proposed utilizing the displacement of the agent to ensure the distances between agents always satisfy predefined distance constraints. This strategy guarantees inter-agent collision avoidance and connectivity preservation throughout the formation. Numerical simulations are conducted to validate the efficacy of the proposed approach.

Adaptive connectivity-preserving formation control with a dynamic event-triggering mechanism

Connectivity preservation for real-life multi-agent systems is key to designing an effective and reliable control algorithm to achieve desired objectives. But the coexistence of system nonlinearities and uncertainties makes it difficult for the algorithm design, and especially in the event-triggered setting, such difficulty becomes severer due to the demand for integration of multiple ingredients. This paper focuses on proposing an adaptive connectivity-preserving formation control strategy that incorporates a dynamic event-triggering mechanism, in the scenario of the unknown control directions and intrinsic nonlinearities coupling with parameter uncertainties. First, a cluster of potential functions serving as control barrier functions are given to maintain the prescribed connectivity of communication graph. Second, two types of dynamic gains (one type is based on a Nussbaum function) are introduced for agents to cope with the system nonlinearities, uncertainties and the adverse effect of the execution error. As such, an adaptive event-triggered formation protocol is constructed such that the desired formation with connectivity preservation is achieved while a positive minimum inter-execution interval is ensured for each agent to avoid Zeno behavior. Particularly, the threshold in the developed event-triggering mechanism is dynamically adjusted online, rather than static, which better improves resource efficiency. A simulation example is given to demonstrate the effectiveness and advantage of the proposed strategy.

Evaluating Water Quality through Macroinvertebrate Diversity and Physicochemical Parameters in the Thamirabarani River Basin

<p style="margin-top:13px; text-align:justify"><span style="font-size:11pt"><span style="line-height:115%"><span style="font-family:Arial,"sans-serif""><span lang="EN" style="font-size:12.0pt"><span style="line-height:115%"><span style="font-family:"Times New Roman","serif"">Aquatic ecosystems in the Thamirabarani River Basin, Tamil Nadu, India, are facing increasingly complex challenges due to climate change, particularly concerning water temperature and dissolved oxygen levels. This study delves into the intricate relationship between these variables and their profound implications for freshwater biodiversity. The rising temperatures and declining dissolved oxygen levels pose escalating threats to the health of aquatic organisms and the stability of ecosystems. To tackle this issue, a hybrid methodology that integrates remote sensing and field data is proposed to calculate the Water Quality Index (WQI) and comprehensively assess ecosystem health. Remote sensing data offer valuable spatial insights, while field measurements ensure accuracy, resulting in robust findings. The study uncovers a significant negative correlation between water temperature and dissolved oxygen levels, highlighting the adverse effects of warming waters on aquatic habitats. Moreover, habitat fragmentation exacerbates climate stressors, adding further challenges to freshwater biodiversity conservation. The findings underscore the urgent need for conservation and adaptive management strategies, including temperature regulation, riparian vegetation enhancement, nutrient pollution management, and habitat connectivity preservation. By implementing these measures, biodiversity loss in freshwater ecosystems can be minimized, ensuring their resilience in the face of ongoing climate change. </span></span></span></span></span></span></p>

Adaptive Neural Cooperative Control of Multirobot Systems With Input Quantization.

This article develops the adaptive neural cooperative control scheme for a group of mobile robots with a limited sensing range in presence of input quantization by a dynamic surface control technique. First, to make the controller design feasible, the original robotic system is transformed into a new fully actuated system using a transverse function. Then, taking into consideration the effects of a hysteresis quantizer, an adaptive neural cooperative controller is developed based on the universal approximation property of the radial basis function neural networks and the connectivity preservation strategy. Furthermore, the proposed control scheme can guarantee that all closed-loop signals are semi-globally uniformly ultimately bounded. Meanwhile, desired constraints are not breached and tracking errors are within the predefined domains. Finally, several simulation results are carried out to testify the feasibility and efficiency of the theoretical findings revealed in this article.

Road Network Intelligent Selection Method Based on Heterogeneous Graph Attention Neural Network

Selecting road networks in cartographic generalization has consistently posed formidable challenges, driving research toward the application of intelligent models. Despite previous efforts, the accuracy and connectivity preservation in these studies, particularly when dealing with road types of similar sample sizes, still warrant improvement. To address these shortcomings, we introduce a Heterogeneous Graph Attention Network (HAN) for road selection, where the feature masking method is initially utilized to assess the significance of road features. Concentrating on the most relevant features, two meta-paths are introduced within the HAN framework: one for aggregating features of the same road type within the first-order neighborhood, emphasizing local connectivity, and another for extending this aggregation to the second-order neighborhood, capturing a broader spatial context. For a comprehensive evaluation, we use a set of metrics considering both quantitative and qualitative aspects of the road network. On road types with similar sample sizes, the HAN model outperforms other models in both transductive and inductive tasks. Its accuracy (ACC) is higher by 1.62% and 0.67%, and its F1-score is higher by 1.43% and 0.81%, respectively. Additionally, it enhances the overall connectivity of the selected network. In summary, our HAN-based method provides an advanced solution for road network selection, surpassing previous approaches in terms of accuracy and connectivity preservation.

Leader-Following Connectivity Preservation and Collision Avoidance Control for Multiple Spacecraft with Bounded Actuation

This paper investigates the distributed formation control of a group of leader-following spacecraft with bounded actuation and limited communication ranges. In particular, connectivity-preserving and collision-avoidance controllers are proposed for the leader with constant or time-varying velocity, respectively. The communication graph between the spacecraft is modeled via a distance-induced proximity graph. By designing a virtual proxy for each spacecraft, the spacecraft–proxy couplings address the actuator saturation constraints. The inter-proxy dynamics incorporated with a bounded artificial potential function fulfill the coordination of all proxies. In addition, the bounded potential function can simultaneously tackle connectivity preservation and collision avoidance problems. The distributed formation controllers are proposed for multiple spacecraft with constant or time-varying velocities relative to the leader. A sliding mode control approach and the proxies’ dynamics are used in the design of a distributed cooperative controller for spacecraft to address the cooperative problem between the followers and the leader. Numerical simulations confirm the effectiveness of the anti-saturation distributed connectivity preservation controller.

Connectivity preservation control for multiple unmanned aerial vehicles in the presence of bounded actuation

This paper proposes a novel multi-unmanned aerial vehicle (UAV) connectivity preservation controller, suitable for scenarios with bounded actuation and limited communication range. According to the hierarchical control strategy, controllers are designed separately for the position and attitude subsystems. A distributed position controller is developed, integrating an indirect coupling control mechanism. The innovative mechanism associates each UAV with a virtual proxy, facilitating connections among adjacent UAVs through these proxies. This structuring assists in managing the actuator saturation constraints effectively. The artificial potential function is utilized to preserve network connectivity and fulfill coordination among all virtual proxies. Additionally, an attitude controller designed for finite-time convergence guarantees that the attitude subsystem adheres precisely to the attitude specified by the distributed position controller. Simulation results validate the efficacy of this distributed formation controller with connectivity preservation under bounded actuation conditions. The simulation results confirm the effectiveness of the distributed connectivity preservation controller with bounded actuation.

Finite-time consensus of second-order multi-agent connectivity preserving based on adaptive sliding mode control

This study addresses the problem of robust finite-time connectivity preserving consensus for second-order multi-agent systems (MASs) with a limited communication range. Considering that the communication ability of agents in practical applications is limited, this study introduces an innovative approach to the consensus protocol, which involves the incorporation of a potential function aimed at ensuring sustained communication connection within a MAS. In addition, a finite-time fault-tolerant consensus protocol for a second-order MAS with actuator additive faults and external disturbances is designed by combining sliding mode control (SMC) and adaptive control. Following the homogeneous theorem and the finite-time consensus theory, this study concludes that, under specific conditions, a MAS can achieve finite-time consensus. Moreover, an advanced control protocol named a super-twisting sliding mode control protocol is introduced to mitigate the undesirable chattering phenomenon in the SMC. Finally, the effectiveness and superiority of the proposed method are verified by numerical examples.

Connectivity Preserving Consensus for Second-Order Heterogeneous MASs With Input Constraints

Connectivity Preserving Consensus for Second-Order Heterogeneous MASs With Input Constraints

Cooperative target fencing of multiple double‐integrator systems with connectivity preservation

AbstractIn this article, we study the cooperative target‐fencing problem of multiple double‐integrator systems over a state‐dependent communication network. We propose a distributed control law to asymptotically fence a moving target while achieving both collision avoidance and connectivity preservation of the vehicles. In particular, a distributed observer is employed by each vehicle to estimate the position and the velocity of the target. Compared with the existing results, our approach can accommodate a larger class of target's trajectories. Furthermore, our control law is more practical since we do not require all vehicles to know the trajectory of the target. The effectiveness of our approach is illustrated by a numerical example.

Predictor‐based collision‐free and connectivity‐preserving resilient formation control for multi‐agent systems under sensor deception attacks

AbstractMalicious attack is a potential threat to collision‐free and connectivity‐preserving formation. In this article, a predictor‐based collision‐free and connectivity‐preserving resilient formation control strategy is proposed for a class of multi‐agent systems under sensor deception attacks. The predictor states are constructed to replace original states in the control strategy, and a novel attack compensator is constructed to suppress sensor deception attacks. Prediction errors, instead of compromised errors, are introduced to update weights of radial basis function neural networks (RBFNNs). To achieve collision avoidance and connectivity preservation, a transformation function in logarithmic form is introduced. To avoid static and dynamic obstacles, an improved artificial potential function (APF) combined with their velocity information is constructed. Furthermore, to solve the local minimum problem in the combining of transformation function and APF, a virtual force is added. Based on the Lyapunov function, all closed‐loop signals are bounded and collision‐free and connectivity‐preserving formation is achieved. The simulation related to a group of quadrotors verifies the effectiveness of the proposed resilient control strategy.

Research on the coupled mechanism of landscape connectivity simulation by integrating multi‐level ecological security patterns and multi‐scenario simulation: A case study of the main urban area of Hangzhou

AbstractIn the context of rapid urbanization, protecting landscape connectivity has become an effective measure to mitigate habitat fragmentation and curb biodiversity decline. However, in the current research on simulating optimization processes, the ecological constraints often set are dispersed, isolated, and fixed. They fail to form a comprehensive protective spatial framework and struggle to align with the multifaceted objectives of future development. This study, taking the main urban area of Hangzhou, China as a case study and employing small mammals as indicator species, utilizes the PLUS model to predict the potential threats to landscape connectivity of biological habitats posed by artificial surface expansion from 2020 to 2035. It constructs a coupled mechanism that integrates multi‐level ecological security patterns (ESPs) and multi‐scenario simulation for landscape connectivity, successfully demonstrating the effectiveness of this mechanism in future landscape connectivity preservation. The results indicate that under the scenarios of business‐as‐usual (BAU), priority given to urban development (PUD), and priority given to ecological protection (PEP), the overall level of landscape connectivity in the main urban area of Hangzhou is projected to decrease by 18.42%, 7.02%, and 4.39% respectively from 2020 to 2035. The reduction in core area is estimated to be 9.08%, 7.85%, and 6.34%, respectively, while highly important patches are expected to decrease by 12.91%, 7.51%, and 5.86%, respectively. Both PEP and PUD scenarios effectively mitigate the degree of landscape connectivity disruption. This study provides valuable insights for the future optimization of landscape connectivity and contributes to biodiversity conservation efforts.

Safe Region Multi-Agent Formation Control With Velocity Tracking

This paper provides a solution to the problem of safe region formation control with reference velocity tracking for a second-order multi-agent system without velocity measurements. Safe region formation control is a control problem where the agents are expected to attain the desired formation while reaching the target region and simultaneously ensuring collision and obstacle avoidance. To tackle this control problem, we break it down into two distinct objectives: safety and region formation control, to provide a completely distributed algorithm. Region formation control is modeled as a high-level abstract objective, whereas safety and actuator saturation are modeled as a low-level objective designed independently, without any knowledge of the former, and being minimally invasive. Our approach incorporates connectivity preservation, actuator saturation, safety considerations, and absence of velocity measurement from other agents with second-order system dynamics which are important constraints in practical applications. Both internal safety for collision avoidance among agents and external safety for avoiding unsafe regions are ensured using exponential control barrier functions. We provide theoretical results for asymptotic convergence and numerical simulation to show the approach’s effectiveness.

Formation Control with Obstacle Avoidance for Heterogeneous Multi-Flying Robots: Connectivity Preservation

Formation Control with Obstacle Avoidance for Heterogeneous Multi-Flying Robots: Connectivity Preservation

Prescribed-time containment control of multi-agent systems subject to collision avoidance and connectivity maintenance

In this paper, the problem of prescribed-time containment control for a second-order multiple leader–follower systems (MLFSs) is studied, in where both collision avoidance and connectivity maintenance of the agents are considered. Firstly, an effective exponential potential field function (EAPF) with constraints based on the estimated distance is designed to achieve collision resistance and connectivity preservation of the agents at a prescribed-time. Secondly, an estimator-based distributed control protocol is proposed, which drives the agents to achieve containment control in a cooperative manner at a prescribed-time. Furthermore, a novel distributed control protocol containing a collision avoidance term and a containment control term is addressed as well, which enables all followers to complete collision avoidance and connectivity maintenance in any prescribed-time and enter the leaders’ convex packet. Finally, the stability of the system is technically analyzed by using Lyapunov theory, and the effectiveness of the presented strategies is verified by several simulations.

Average-rendezvous with connectivity preservation for first-order multiagent systems with constant reference signals

Average-rendezvous problem with connectivity preservation of constant reference signals is investigated for first-order multiagent systems. According to a constructive potential function, a proportional–integral average-rendezvous algorithm is proposed to make agents converge to the average value of constant reference signals as well as the network connectivity is preserved all the time. Sufficient convergence conditions are obtained for the algorithm by designing the proper Lyapunov functions. Numerical examples illustrate the correctness of theoretical results.

Fish conservation in streams of the agrarian Mississippi Alluvial Valley: conceptual model, management actions, and field verification

The effects of agriculture and flood control practices accrued over more than a century have impaired aquatic habitats and their fish communities in the Mississippi Alluvial Valley, the historic floodplain of the Lower Mississippi River prior to leveeing. As a first step to conservation planning and adaptive management, we developed and tested a conceptual model of how changes to this floodplain have affected stream environments and fish assemblages. The model is deliberately simple in structure because it needs to be understood by stakeholders ranging from engineers to farmers who must remain engaged to ensure effective conservation. Testing involved multivariate correlative analyses that included descriptors of land setting, water quality, and fish assemblages representing 376 stream samples taken over two decades and ranging in Strahler stream order from 1 to 8. The conceptual model was adequately corroborated by empirical data, but with unexplained variability that is not uncommon in field surveys where gear biases, temporal biases, and scale biases prevent accurate characterizations. Our conceptual model distinguishes three types of conservation actions relevant to large agricultural floodplains: reforestation of large parcels and riparian zone conservation, in-channel interventions and connectivity preservation, and flow augmentation. Complete restoration of the floodplain may not be an acceptable option to the agriculture community. However, in most cases the application of even the most basic measures can support the return of sensitive aquatic species. We suggest that together these types of conservation actions can bring improved water properties to impacted reaches, higher reach biodiversity, more intolerant species, and more rheophilic fishes.

UDE-Based Distributed Formation Control for MSVs With Collision Avoidance and Connectivity Preservation

Limited computational resource is one of features of the embedded system including unmanned marine surface vehicle (MSV). Under this practical constraint, we aim to develop a distributed formation control algorithm for a group of uncertain MSVs, whose computational burden is low. The uncertainty and disturbance estimator (UDE) is employed to compensate for the modeling uncertainties, the unknown environmental disturbances, and the unavailable derivative of the virtual control inputs, such that the formation errors converge asymptotically to zero. Meanwhile, the prescribed performance control technique is applied to ensure that the convergence rates of the formation errors are faster than predefined values. Additionally, collision avoidance and connectivity preservation among the neighboring vehicles are guaranteed, while the obstacle avoidance is also ensured. As no parameter update law is required to calculate, the computational burden is reduced significantly. The effectiveness of the proposed UDE-based formation control algorithm is validated through comparative simulation.

Fuzzy adaptive time‐varying formation control of USVs with actuator faults

SummaryThis paper investigates the fuzzy adaptive time‐varying formation control problem for fully‐actuated unmanned surface vehicles (USVs) systems. The studied USVs systems include uncertain dynamics and actuator faults. Fuzzy logic systems (FLSs) and disturbance observer are employed to estimate uncertain nonlinear dynamics in system model and external time‐varying disturbances, respectively. Meanwhile, the prescribed performance control (PPC) technique is applied to construct the constraint requirements of collision avoidance and connectivity preservation in time‐varying formation control. Additionally, a new robust adaptive fault‐tolerant control (FTC) algorithm is presented. Hence, by the aid of adaptive backstepping technique with performance functions, a robust fuzzy adaptive time‐varying formation FTC scheme of time‐varying formation is developed. The proposed formation control scheme not only has the advantages of avoiding collision and preserving connectivity, but also ensures all the signals are uniformly ultimately bounded (UUB). Finally, the simulation results are provided to demonstrate the effectiveness of the proposed approach.

Connectivity‐preserving consensus: An adaptive event‐triggered strategy

SummaryThe connectivity of communication graph is indispensable for consensus of multi‐agent systems (MASs), which in many applications (e.g., wireless sensor) depends on the relative distances between agents. But, in the adaptive setting particularly with system nonlinearities and event‐triggered communication, it is rather difficult to enforce the relative distances within the limited range for the connectivity. This paper focuses on developing an adaptive event‐triggered control strategy with connectivity preservation in the context of nonidentical unknown control coefficients and heterogeneous nonlinearities coupling with parameter uncertainties. First, a group of potential functions are introduced acting as control barrier functions to constrain the relative distances between agents within the limited range for all time. Also, two dynamic gains are specialized for each agent to handle the system uncertainties, system nonlinearities and negative effect of the execution error. Then, an adaptive event‐triggered protocol is designed for each agent such that the connectivity‐preserving consensus of MASs is achieved and Zeno behavior is excluded. Moreover, an extended study is conducted on a leader‐following scenario. Two simulation examples illustrate the effectiveness of the proposed event‐triggered control strategy.