Tracking Protocol Research Articles

Observer-Based Fixed-Time Consensus Tracking for a Class of Nonlinear Multi-Agent Systems

In this paper, the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems (MASs) with uncertainties and external disturbances is addressed. To solve this problem, a new fixed-time consensus tracking protocol with disturbance rejection abilities is proposed that consists of a fixed-time distributed observer (FTDO), a fixed-time disturbance observer (FDO), and a nonsmooth backstepping controller with lumped disturbance compensation (NBCDC). The fixed-time stabilities are analyzed correspondingly. Firstly, an FTDO is designed to estimate a leader’s output by using the topology of communication networks for each follower. Second, an FDO is developed to observe the lumped disturbances composed of model uncertainties and external disturbances. Finally, an NBCDC is proposed for improving the closed-loop performance. The simulation results show that the proposed method is effective.

Observer-based adaptive time-varying formation tracking of one-sided Lipschitz nonlinear multi-agent systems

In this article, the problem of time-varying formation (TVF) tracking for nonlinear multi-agent systems (MASs) is investigated. The agent dynamics are described by one-sided Lipschitz (OSL) and quadratic inner-boundedness (QIB) function. Adaptive continuous TVF tracking protocols for nonlinear MASs are proposed. Compared to prior nonlinear system, this approach is more general and less conservative than nonlinear system with large Lipschitz constant. In addition, the continuous protocols are proposed to avoid undesirable chattering from non-zero inputs of the leader. Finally, the expected theoretical results are achieved through effective numerical simulations.

Resilient Time-Varying Formation Tracking Control for General Linear Multiagent Systems With a Nonautonomous Leader and Adversarial Followers.

This article is concerned with resilient formation tracking problems for general linear multiagent systems, where the leader's control input is unavailable to all the followers and partial followers' behaviors are malicious due to the node attacks. Despite the presence of the nonautonomous leader and the adversarial followers, the remaining benign followers are still expected to track the leader's trajectory with the prescribed time-varying formation. To this end, a resilient scheme comprising an attack detection and isolation strategy and a formation tracking protocol is proposed. The detection strategy enables every benign follower to identify its adversarial neighbors with two-hop communication information, as long as the underlying topology meets given conditions. Then, the detected adversarial agents are directly removed to avoid the spread of their influence, which induces a new problem called node loss. To accommodate possible node loss events, the designed tracking protocol is independent of certain global knowledge, and its convergence is demonstrated by means of the impulsive Lyapunov functions. Finally, the proposed resilient scheme is verified by two simulation examples.

Theory and experiment on distributed output formation tracking of unmanned aerial and ground vehicle swarm systems over jointly connected digraphs

This paper studies the distributed output formation tracking control problem of the unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) swarm systems, where the UAV swarm cooperatively tracks the output trajectory of the UGV in a formation under directed jointly connected communication networks. A three-layer formation tracking protocol is proposed. Firstly, a novel distributed observer using neighbor interactions is designed for each UAV to estimate the states of the UGV with parameterized inputs over periodic jointly connected digraphs. Next, based on the observation result and output regulation theory, a virtual reference system that tracks the trajectory of the UGV in the desired formation is constructed to generate reference states for each UAV. Then based on the differential flatness of UAVs, a geometric controller is utilized for UAVs to track the reference states and form the formation. An algorithm to determine the gain matrices of the protocol is also presented while the convergence of the system is analyzed. Finally, an experiment platform with three quadrotor UAVs and one UGV is built. The effectiveness of the proposed protocol is validated both by the simulation and experiment.

Rapeseed Flower Counting Method Based on GhP2-YOLO and StrongSORT Algorithm.

Accurately quantifying flora and their respective anatomical structures within natural ecosystems is paramount for both botanical breeders and agricultural cultivators. For breeders, precise plant enumeration during the flowering phase is instrumental in discriminating genotypes exhibiting heightened flowering frequencies, while for growers, such data inform potential crop rotation strategies. Moreover, the quantification of specific plant components, such as flowers, can offer prognostic insights into the potential yield variances among different genotypes, thereby facilitating informed decisions pertaining to production levels. The overarching aim of the present investigation is to explore the capabilities of a neural network termed GhP2-YOLO, predicated on advanced deep learning techniques and multi-target tracking algorithms, specifically tailored for the enumeration of rapeseed flower buds and blossoms from recorded video frames. Building upon the foundation of the renowned object detection model YOLO v8, this network integrates a specialized P2 detection head and the Ghost module to augment the model's capacity for detecting diminutive targets with lower resolutions. This modification not only renders the model more adept at target identification but also renders it more lightweight and less computationally intensive. The optimal iteration of GhP2-YOLOm demonstrated exceptional accuracy in quantifying rapeseed flower samples, showcasing an impressive mean average precision at 50% intersection over union metric surpassing 95%. Leveraging the virtues of StrongSORT, the subsequent tracking of rapeseed flower buds and blossom patterns within the video dataset was adeptly realized. By selecting 20 video segments for comparative analysis between manual and automated counts of rapeseed flowers, buds, and the overall target count, a robust correlation was evidenced, with R-squared coefficients measuring 0.9719, 0.986, and 0.9753, respectively. Conclusively, a user-friendly "Rapeseed flower detection" system was developed utilizing a GUI and PyQt5 interface, facilitating the visualization of rapeseed flowers and buds. This system holds promising utility in field surveillance apparatus, enabling agriculturalists to monitor the developmental progress of rapeseed flowers in real time. This innovative study introduces automated tracking and tallying methodologies within video footage, positioning deep convolutional neural networks and multi-target tracking protocols as invaluable assets in the realms of botanical research and agricultural administration.

Observer-based time-varying formation-containment tracking of general linear multi-agent systems with input saturation

In this article, we study the time-varying formation-containment (TVFC) tracking problem for linear multi-agent systems (MASs) and take the input saturation problem of the systems into account. An observer-based TVFC tracking protocol is proposed. It has been proven that the real leaders can realize the expected formation and track the virtual leader’s trajectory, and followers can get into the convex envelope spanned by the leaders. In addition, to avoid unexpected large chattering caused by nonzero input, we propose a continuous protocol. Under this protocol, each error is uniformly ultimately bounded and is able to converge to any small zero neighborhood. At the end, the feasibility of the TVFC theory is demonstrated by simulation examples.

Time‐varying group formation tracking control for multi‐agent systems using distributed multi‐sensor multi‐target filtering with intermittent observations

AbstractTime‐varying group formation tracking control problems for multi‐agent systems are investigated based on distributed multi‐sensor multi‐target filtering with intermittent observations. First, in order to estimate the states of multiple targets under the phenomenon of intermittent observations accurately, a distributed multi‐sensor multi‐target filtering algorithm is proposed based on cubature Kalman filtering. Second, a time‐varying group formation tracking protocol is designed for multi‐agent systems by using the state estimations obtained from the filtering algorithm and the neighboring interaction. The protocol enables multi‐agent systems to form time‐varying subformations and track multiple targets in the same subgroups, respectively. Third, the boundedness of the error covariance matrices is proved under the condition that the observation probability is higher than the minimum threshold. Then the estimation errors of the filtering algorithm are proved to be stochastically bounded by introducing a stochastic process. Furthermore, the boundedness of the group formation tracking errors is proved. Finally, a numerical example is used to verify the performance of the proposed algorithm and protocol.

Distributed Neurodynamics-Based Backstepping Optimal Control for Robust Constrained Consensus of Underactuated Underwater Vehicles Fleet.

Robust constrained formation tracking control of underactuated underwater vehicles (UUVs) fleet in 3-D space is a challenging but practical problem. To address this problem, this article develops a novel consensus-based optimal coordination protocol and a robust controller, which adopts a hierarchical architecture. On the top layer, the spherical coordinate transform is introduced to tackle the nonholonomic constraint, and then a distributed optimal motion coordination strategy is developed. As a result, the optimal formation tracking of UUVs fleet can be achieved, and the constraints are fulfilled. To realize the generated optimal commands better and, meanwhile, deal with the underactuation, at the lower-level control loop a neurodynamics-based robust backstepping controller is designed, and in particular, the issue of "explosion of terms" appearing in conventional backstepping-based controllers is avoided and control activities are improved. The stability of the overall UUVs formation system is established to ensure that all the states of the UUVs are uniformly ultimately bounded in the presence of unknown disturbances. Finally, extensive simulation comparisons are made to illustrate the superiority and effectiveness of the derived optimal formation tracking protocol.

Observer-based guaranteed-cost bipartite time-varying formation tracking control for multiagent systems subject to communication delays

The paper centers on the guaranteed-cost bipartite time-varying formation tracking control for multiagent systems with nonuniform time-varying communication delays under the framework of a distributed observer. An integral quadratic cost function is presented, founded on formation tracking and observation error. Firstly, distributed state observers, using the relative measurement output between neighbors, are established so that the leader and follower can accurately estimate each agent's unmeasurable state. Subsequently, a bipartite formation tracking protocol is proposed, incorporating estimation information and nonuniform time-varying communication delays. This protocol aims to achieve bipartite time-varying formation tracking for multiagent systems. Next, a new augmented Lyapunov-Krasovskii functional with delay-product and triple integral terms is constructed. By integrating the second-order Bessel-Legendre inequality technique, the delay-dependent reciprocally convex combination inequality method, and the free weight matrix technique, a new guaranteed-cost bipartite time-varying formation tracking criterion is developed, offering less conservatism. Compared to certain existing delay conditions, the stability conditions assure a greater allowable upper bound of delay. Finally, a numerical example is conducted to confirm the validity and superiority of the theoretical findings.

Time‐varying output group formation‐containment tracking control for heterogeneous multi‐agent system

AbstractThe time‐varying output group formation‐containment tracking (TVOGFCT) problem of discrete‐time heterogeneous multi‐agent system (MAS) is investigated in this paper. Assuming the MAS consists of multiple tracking leaders, formation leaders, and followers, and all the agents are divided into several groups. Firstly, to estimate the convex combination of tracking leaders in the same group, the distributed observers are designed for the formation leaders, and the observer‐based formation tracking protocols are also presented to make formation leaders realize the desired time‐varying group formation while tracking the convex combination of tracking leaders. Then, two types of observers are proposed to estimate the convex combination of tracking information and formation functions, based on which the containment tracking protocols are designed for the followers of each group. By using output regulation theory and Lyapunov theory, it is illustrated that the designed protocols can make the MAS realize TVOGFCT. Finally, the simulation results prove the correctness of the theoretical analysis.

Leader-following consensus tracking control for fractional-order multi-motor systems via disturbance-observer

Abstract The leader-following consensus tracking control of fractional-order (FO) multi-motor systems (FOMMSs) in the presence of exogenous disturbances is investigated. It is widely recognized that FO models are better than integer-order (IO) ones for representing systems with memory effects. Therefore, studying the consensus tracking control of FOMMSs is essential. In this paper, a consensus tracking protocol is developed using a disturbance-observer and state feedback to deal with unknown exogenous disturbances. The closed-loop system stability is analyzed via Lyapunov and graph theory. Novel sufficient conditions for the stabilization of each motor are derived in the form of linear matrix inequalities. Simulation results illustrate the validity and efficacy of the proposed consensus protocol, namely its strong synchronization ability and robustness.

Observer‐based adaptive time‐varying bipartite formation tracking of multi‐agent systems with multiple nonautonomous leaders

AbstractIn this article, the problem of bipartite time‐varying formation (BTVF) tracking for multi‐agent systems (MASs) under signed digraphs is investigated, in which the inputs of leaders are unknown and bounded. A novel kind of adaptive nonsmooth BTVF tracking protocol for MASs is proposed that did not utilize eigenvalue of Laplacian matrix. Based on the state observer, the problem that the system states are not measurable is solved. In addition, in order to avoid undesirable chattering caused by leaders' nonzero inputs, continuous protocols are proposed. And in this case, the error is uniformly ultimately bounded. Lyapunov method reflects the convergence analysis of the submitted protocols. At last, the desired theoretical results are achieved on a multirobot system.

Formation tracking control in open multiagent systems with general linear dynamics

This paper studies the formation tracking problem of the so-called open multiagent systems. In these systems, agents can freely join or leave at any time, i.e. the system sizes are changeable. To achieve formation tracking control in these systems, we propose a general theoretical analysis framework that consists of a formation adjustment strategy and a formation tracking protocol. Therein, the former is used to adjust the predefined task-oriented formation shape to the varying size of the system. This strategy is built on the existing scalable self-healing idea and then modified by a size estimation method. The latter is used to drive the present followers to form the adjusted formation and track a leader. To accommodate undirected and directed graphs, two distributed formation tracking protocols are designed respectively. Due to possible agent migration, the designed tracking protocols are endowed with self-adaptive ability, i.e. without depending on global topology information. Then, their convergence properties are analysed using the Lyapunov theory. Finally, two simulations are presented to verify the effectiveness of the proposed framework.

Abstract 471: Attenuation of circulating miR-17-5p, miR-20b-5p, and miR-106a-5p in low-risk prostate cancer patients following proton therapy

Abstract Introduction: Liquid biopsies offer a novel approach to diagnose, predict cancer outcomes, and monitor treatment response by analyzing tumor-derived substances. Circulating cell-free microRNAs (miRNAs) show clinical promise as biomarkers within prostate cancer (PCa) and have been implicated with PCa prognosis and outcomes. However, their potential for monitoring and assessing radiotherapy (RT) treatment response remains understudied. Understanding miRNA expression changes during RT is crucial, as they impact RT efficacy by directly affecting genes and proteins within RT-response pathways. Aim: This study aimed to profile the expression of three oncogenes, miR-17-5p, miR-20b-5p, and miR-106a-5p and to determine their association with PCa risk groups in patients receiving proton therapy (PT). Patients and Methods: Plasma was obtained from the University of Florida Health Proton Therapy Institute Outcomes Tracking Protocol biobank. Plasma was collected from men diagnosed with localized PCa without metastatic disease at three time points: prior to PT (PRE-PT), at 4 weeks following the start of PT (4WKSPD1), and at 8 weeks following the start of PT (8WKSPD1). The pilot study consisted of 38 patients, with 23 categorized as low-risk and 15 categorized as high-risk for PCa. MiRNA expression levels were evaluated using reverse transcription-polymerase chain reaction and quantified using the Livak method. Results: The study revealed a downregulation of miR-17-5p in response to PT, with median gene expression levels decreasing from 0.73 at PRE-PT to 0.587 at 8WKSPD1. Low-risk PCa patients also showed distinct miRNA expression changes with all three miRNAs (miR-17-5p, miR-20b-5p, and miR-106a-5p) downregulated from 0.953, 1.037, and 1.010 at PRE-PT to 0.398, 0.216, and 0.298 at 8WKSPD1, respectively. Statistical analysis using a Kruskal-Wallis test followed by a Dunn's post-hoc test identified significant differences (p=0.035) specifically between PRE-PT and 8WKSPD1 for miR-17-5p. Conclusion: The study revealed that PT led to a time-dependent reduction in miRNA levels, indicating a higher responsiveness in low-risk compared to high-risk PCa patients. This differential response highlights miR-17-5p, miR-20b-5p, and miR-106a-5p as potential PT response biomarkers, with clinical implications for personalizing PCa treatment. These results underscore the necessity for further validation of these miRNAs to maximize their clinical utility. Citation Format: Johnny Velasquez, Curtis Bryant, Nancy Mendenhall, Luisel Ricks-Santi. Attenuation of circulating miR-17-5p, miR-20b-5p, and miR-106a-5p in low-risk prostate cancer patients following proton therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 471.

Formation fault-tolerant control for multiple UAVs with external disturbances

PurposeThe purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.Design/methodology/approachFirst, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.FindingsIt achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.Originality/valueA formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Fixed-Time Fault-Tolerant Consensus Control for High-Order Nonlinear Multiagent Systems Under Directed Topology

This paper addresses the fixed-time fault-tolerant consensus control problem for high-order nonstrict-feedback nonlinear multi-agent systems under directed topology. A distributed high-order fixed-time observer is proposed to obtain the accurate estimations of the full states of the leader. Different from the fixed-time observer design methods, a much more concise estimate for the upper bound of the convergence time is provided. Based on the fixed-time observer and adding a power technique, a fixed-time tracking protocol is designed for a group of followers subject to unknown nonidentical dynamics and unpredictable actuation faults. It is shown that there is no need to know the information of the nonstrict-feedback nonlinear dynamics, the control gains, and the actuation faults in the control design and implementation completely, which is deemed favorable in practice. Simulation results are provided to validate the effectiveness of the developed control scheme.

Bipartite consensus tracking of second-order fractional-order multi-agent systems on directed signed graphs

This paper studies the bipartite consensus tracking problems of fractional-order multi-agent systems on directed signed graphs. Each agent is modelled as a second-order fractional-order dynamics with the order belonging to ( 0 , 1 ] , and the cooperative and competitive interactions between the agents coexist in the systems. Two distributed bipartite consensus tracking protocols are proposed for the systems based on continuous information and sampled information, respectively. Under the assumption that the directed signed graph is structurally balanced, it is shown that the second-order fractional-order multi-agent systems can achieve the bipartite consensus tracking if the feedback coefficients are chosen appropriately. Finally, several simulations are provided to verify the effectiveness of the theoretical results.

Ambient and focal attention during complex problem-solving: preliminary evidence from real-world eye movement data.

Time course analysis of eye movements during free exploration of real-world scenes often reveals an increase in fixation durations together with a decrease in saccade amplitudes, which has been explained within the two visual systems approach, i.e., a transition from ambient to focal. Short fixations and long saccades during early viewing periods are classified as ambient mode of vision, which is concerned with spatial orientation and is related to simple visual properties such as motion, contrast, and location. Longer fixations and shorter saccades during later viewing periods are classified as focal mode of vision, which is concentrated in the foveal projection and is capable of object identification and its semantic categorization. While these findings are mainly obtained in the context of image exploration, the present study endeavors to investigate whether the same pattern of interplay between ambient and focal visual attention is deployed when people work on complex real-world tasks-and if so, when? Based on a re-analysis of existing data that integrates concurrent think aloud and eye tracking protocols, the present study correlated participants' internal thinking models to the parameters of their eye movements when they planned solutions to an open-ended design problem in a real-world setting. We hypothesize that switching between ambient and focal attentional processing is useful when solvers encounter difficulty compelling them to shift their conceptual direction to adjust the solution path. Individuals may prefer different attentional strategies for information-seeking behavior, such as ambient-to-focal or focal-to-ambient. The observed increase in fixation durations and decrease in saccade amplitudes during the periods around shifts in conceptual direction lends support to the postulation of the ambient-to-focal processing; however, focal-to-ambient processing is not evident. Furthermore, our data demonstrate that the beginning of a shift in conceptual direction is observable in eye movement behavior with a significant prolongation of fixation. Our findings add to the conclusions drawn from laboratory settings by providing preliminary evidence for ambient and focal processing characteristics in real-world problem-solving.

Time-varying formation tracking control for multi-agent systems using distributed multi-sensor multi-target filtering

Time-varying formation tracking control issues for multi-agent systems are investigated based on the distributed multi-sensor multi-target filtering algorithm. In order to estimate the states of targets, a distributed multi-sensor multi-target filtering algorithm based on cubature Kalman filtering is investigated. Subsequently, the state estimations calculated by the filtering algorithm are used to design a time-varying formation tracking protocol for multi-agent systems, enabling the agents to form a time-varying formation and track the convex combination of uncooperative targets. The estimation errors of the filtering algorithm are proved to be bounded in mean square by introducing a stochastic process and the boundedness of the formation tracking errors is further proved. Simulation results illustrates the effectiveness of the proposed algorithm and protocol.

A semi-automated cell tracking protocol for quantitative analyses of neutrophil swarming to sterile and S. aureus contaminated bone implants in a mouse femur model.

Implant-associated osteomyelitis remains a major orthopaedic problem. As neutrophil swarming to the surgical site is a critical host response to prevent infection, visualization and quantification of this dynamic behavior at the native microenvironment of infection will elucidate previously unrecognized mechanisms central to understanding the host response. We recently developed longitudinal intravital imaging of the bone marrow (LIMB) to visualize host cells and fluorescent S. aureus on a contaminated transfemoral implant in live mice, which allows for direct visualization of bacteria colonization of the implant and host cellular responses using two-photon laser scanning microscopy. To the end of rigorous and reproducible quantitative outcomes of neutrophil swarming kinetics in this model, we developed a protocol for robust segmentation, tracking, and quantifications of neutrophil dynamics adapted from Trainable Weka Segmentation and TrackMate, two readily available Fiji/ImageJ plugins. In this work, Catchup mice with tdTomato expressing neutrophils received a transfemoral pin with or without ECFP/EGFP-expressing USA300 methicillin-resistant Staphylococcus aureus (MRSA) to obtain 30-minute LIMB videos at 2-, 4-, and 6-hours post-implantation. The developed semi-automated neutrophil tracking protocol was executed independently by two users to quantify the distance, displacement, speed, velocity, and directionality of the target cells. The results revealed high inter-user reliability for all outcomes (ICC > 0.96; p > 0.05). Consistent with the established paradigm on increased neutrophil swarming during active infection, the results also demonstrated increased neutrophil speed and velocity at all measured time points, and increased displacement at later time points (6 hours) in infected versus uninfected mice (p < 0.05). Neutrophils and bacteria also exhibit directionality during migration in the infected mice. The semi-automated cell tracking protocol provides a streamlined approach to robustly identify and track individual cells across diverse experimental settings and eliminates inter-observer variability.