Search Results (2,180)

To increase the hit efficiency and lethality of a flight vehicle, it is necessary to consider the vehicle’s guidance law concerning both impact time and angle constraints. In this study, a novel and straightforward impact time and angle control guidance law that is independent of time-to-go and small angle approximations is proposed with two stages using a data-driven method and proportional navigation guidance. First, a proportional navigation guidance-based impact angle control guidance law is designed for the second stage. Second, from various initial conditions on the impact angle control guidance simulation with various initial conditions, the input and output datasets are obtained to build a mapping network. Using the neural network technique, a mapping network model that can output the ideal flight path angle in flight is constructed for impact time control in the first stage. The proposed impact time and angle control guidance law reduces to the proportional navigation guidance law when the flight path angle error converges to zero. The simulation results show that the proposed guidance law delivers excellent performance under various conditions (including cooperative attack) and features better acceleration performance and less control energy than does the comparative impact time and angle control guidance law. The results of this research are expected to supplement those exploring various paradigms to solve the impact time and angle control guidance problem, as concluded in the current literature. Full article

Underwater wireless sensor networks are gaining popularity since supporting a broad range of applications, both military and civilian. Wireless acoustics is the most widespread technology adopted in underwater networks, the realization of which must face several challenges induced by channel propagation like signal attenuation, multipath and latency. In order to address such issues, the attention of researchers has recently focused on the concept of cooperative communication and networking, borrowed from terrestrial systems and to be conveniently recast in the underwater scenario. In this paper, we present a comprehensive literature review about cooperative underwater wireless sensor networks, investigating how nodes cooperation can be exploited at the different levels of the network protocol stack. Specifically, we review the diversity techniques employable at the physical layer, error and medium access control link layer protocols, and routing strategies defined at the network layer. We also provide numerical results and performance comparisons among the most widespread approaches. Finally, we present the current and future trends in cooperative underwater networks, considering the use of machine learning algorithms to efficiently manage the different aspects of nodes cooperation. Full article

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm. Full article

With the rapid development of new-generation cyber–physical system (CPS) technologies, the smart operation and management of the broad bean harvesting system are enabled. This paper proposed a smart broad bean harvesting system (SBHS) and a self-adaptive control method based on CPS technologies. Firstly, the overall architecture of the SBHS is designed, which consists of four main components, namely optimal intelligent perception environment configuration, digital twin model construction, virtual simulation and real-time optimization, self-adaptive adjustment and control. Then, three key enabling technologies are discussed in detail, namely, intelligent perception environment configuration for the SBHS, digital twin model construction for the SBHS, colored Petri net (CPN)-based self-adaptive analysis and control of the harvesting system. Lastly, a proof-of-concept experiment based on a cooperative company is presented to illustrate the main work logic and advantage of the proposed SBHS. After the edge–cloud cooperative intelligent harvesting environment is configured, the CPN model for the workflow of the SBHS is created to analyze and optimize the harvesting processes. In addition, a management and control platform are developed to further illustrate the implementation of the proposed SBHS and the self-adaptive control method. Full article

This paper investigates robust constrained cooperative control for multiple trains, taking into account disturbances, velocity and control input constraints, and nonlinear operation resistances. A robust constrained cooperative control algorithm is employed, utilizing position information from neighboring trains to ensure each train operates within the desired formation. The effects of external disturbances are examined through multiple transformations and the convexity of stochastic matrices, resulting in an error bound for the final relative positions. This error boundary is correlated with the parameters of the system matrix, initial state conditions, and disturbance amplitudes. The theoretical findings are substantiated with a numerical example. Full article

Tuberculosis (TB) remains a significant public health challenge in Nigeria, with high rates of transmission and low case detection rates. This paper presents the challenges of screening and investigation of contacts of patients with TB in Oyo and Osun State, Nigeria. This descriptive-qualitative study was conducted in eight Local Government Areas with high TB burdens. Twenty-four focus group discussions and 30 key informant interviews were conducted among TB patients, household TB contacts, and government TB staff, among others. Respondents ages ranged from 17–85 years with a mean of 42.08 ± 14.9 years, and (4.0%) had a postgraduate degree. This study identified that the majority of TB contacts who tested negative for TB were unwilling to be placed on TB preventive therapy because of the belief that only a sick person should take drugs. Also, hostility from the TB contacts to the contact tracers during the house-to-house screening of presumptive TB cases due to community stigma associated with TB was another existing gap reported in TB contact investigations. The findings emphasise the importance of tailored approaches in TB prevention and control, addressing challenges in testing and contact investigations; this necessitates investments in community engagement strategies to enhance the cooperation of TB contacts. Full article

This paper addresses the active target protection problem in a three-player (Target–Attacker–Defender, TAD) conflict by proposing a cooperative integrated guidance and control (IGC) strategy. Unlike previous studies that have designed guidance and control loops separately, this work establishes an IGC model by linearizing both the translational motion and the rotational motion of the vehicles, thereby generating actuator commands directly. This model integrates the kinematics and short-period dynamics, providing a more comprehensive and accurate representation of the vehicles’ characteristics. Based on the linearization and order reduction, differential game theory and the sweep method are employed to derive and analytically solve the Riccati differential equation, yielding an optimal control strategy with an explicit expression. The theoretical rigor of the proposed approach is ensured through a proof of optimality sufficiency. Furthermore, factors influencing the computational accuracy of the Riccati equation solution, including the singular values of the control matrix and condition numbers of the solution matrix, are analyzed. Taking into account the dynamic response and limitations of the actuators, numerical simulations demonstrate the effectiveness and superiority of the proposed IGC strategy in intercepting the attacker and protecting the target compared to traditional separated guidance and control designs. Full article

Different from an ordinary project, a large group mission like the unmanned aerial vehicle (UAV) swarm cooperative strike mission is performed by multiple executors and needs to be strictly carried out according to the plan. Because of the complex cooperative relationships between the sub-missions that make up a large mission, a small disturbance may cause a delay in the entire plan. Therefore, the mission process must be precisely controlled in real time to resist disturbances and ensure that the mission proceeds as planned. To address the real-time process control problem of large group missions, we propose a novel dual-code group network plan diagram model that enables plan description and process tracking for complex group missions. Additionally, a mission process closed-loop feedback control system is designed that models the mission process control problem as a mapping from the mission state observation to plan adjustment. Furthermore, an analytic-based mission process control strategy is proposed and rigorously proven to converge and be effective, as well as demonstrate the maximum anti-disturbance capability. Finally, the control strategy is tested on a UAV swarm cooperative strike mission containing 56 sub-missions. The simulation results demonstrate that the proposed control strategy is capable of achieving high, fast, and accurate control for the mission process and enhancing the anti-disturbance capability of the plan by adjusting the mission plan in real time. This will provide a valuable reference for the management of large group missions. Full article

To address the limitations of inadequate real-time performance and robustness encountered in estimating the pose of non-cooperative spacecraft during on-orbit missions, a novel method of feature point distribution selection learning is proposed. This approach utilizes a non-coplanar key point selection network with uncertainty prediction, pioneering in its capability to accurately estimate the pose of non-cooperative spacecraft, thereby representing a significant advancement in the field. Initially, the feasibility of designing a non-coplanar key point selection network was analyzed based on the influence of sensor layout on the pose measurement. Subsequently, the key point selection network was designed and trained, leveraging images extracted from the spacecraft detection network. The network detected 11 pre-selected key points with distinctive features and was able to accurately predict their uncertainties and relative positional relationships. Upon selection of the key points exhibiting low uncertainty and non-coplanar relative positions, we utilized the EPnP algorithm to achieve accurate pose estimation of the target spacecraft. Our experimental evaluation on the SPEED dataset, which comes from the International Satellite Attitude Estimation Competition, validates the effectiveness of our key point selection network, significantly enhancing estimation accuracy and timeliness compared to other monocular spacecraft attitude estimation methods. This advancement provides robust technological support for spacecraft guidance, control, and proximity operations in orbital service missions. Full article

Background and Objectives: Despite rapid advances in targeted therapies for renal cell carcinoma (RCC), bone metastases remain a major problem that significantly increases morbidity and reduces patients’ quality of life. Conventional fractionated radiotherapy (CF-RT) is known to be an important local treatment option for bone metastases; however, bone metastases from RCC have traditionally been considered resistant to CF-RT. We aimed to investigate the effectiveness of CF-RT for symptomatic bone metastasis from RCC and identify the predictive factors associated with treatment outcomes in the targeted therapy era. Materials and Methods: Between January 2011 and December 2023, a total of 73 lesions in 50 patients treated with a palliative course of CF-RT for symptomatic bone metastasis from RCC were evaluated, and 62 lesions in 41 patients were included in this study. Forty-five lesions (72.6%) were treated using targeted therapy during CF-RT. The most common radiation dose fractionations were 30 gray (Gy) in 10 fractions (50%) and 39 Gy in 13 fractions (16.1%). Results: Pain relief was experienced in 51 of 62 lesions (82.3%), and the 12-month local control (LC) rate was 61.2%. Notably, 72.6% of the treatment course in this study was combined with targeted therapy. The 12-month LC rate was 74.8% in patients who received targeted therapy and only 10.9% in patients without targeted therapy (p < 0.001). Favorable Eastern Cooperative Oncology Group performance status (p = 0.026) and pain response (p < 0.001) were independent predictors of improved LC. Radiation dose escalation improved the LC in radiosensitive patients. A consistent treatment response was confirmed in patients with multiple treatment courses. Conclusions: CF-RT enhances pain relief and LC when combined with targeted therapy. Patients who responded well to initial treatment generally showed consistent responses to subsequent CF-RT for additional painful bone lesions. CF-RT could therefore be an excellent complementary local treatment modality for targeted therapy. Full article

Introduction: Bone sarcoma or direct pelvic carcinoma invasion of the sacrum represent indications for partial or total sacrectomy. The aim was to describe the oncosurgical management and complication profile and to analyze our own outcome results following sacrectomy. Methods: In a retrospective analysis, 27 patients (n = 8/10/9 sarcoma/chordoma/locally recurrent rectal cancer (LRRC)) were included. There was total sacrectomy in 9 (incl. combined L5 en bloc spondylectomy in 2), partial in 10 and hemisacrectomy in 8 patients. In 12 patients, resection was navigation-assisted. For reconstruction, an omentoplasty, VRAM-flap or spinopelvic fixation was performed in 20, 10 and 13 patients, respectively. Results: With a median follow-up (FU) of 15 months, the FU rate was 93%. R0-resection was seen in 81.5% (no significant difference using navigation), and 81.5% of patients suffered from one or more minor-to-moderate complications (especially wound-healing disorders/infection). The median overall survival was 70 months. Local recurrence occurred in 20%, while 44% developed metastases and five patients died of disease. Conclusion: Resection of sacral tumors is challenging and associated with a high complication profile. Interdisciplinary cooperation with visceral/vascular and plastic surgery is essential. In chordoma patients, systemic tumor control is favorable compared to LRRC and sarcomas. Navigation offers gain in intraoperative orientation, even if there currently seems to be no oncological benefit. Complete surgical resection offers long-term survival to patients undergoing sacrectomy for a variety of complex diseases. Full article

Cooperation plays a crucial role in children’s social development and adaptation. This study designed a cooperative constructive play (CCP) intervention based on the Anji Play teaching model and evaluated its effectiveness in a quasi-experimental design involving 60 rural Chinese children aged 5–6 years. Participants were divided into an experimental group, which engaged in 12 weeks of CCP, and a control group, which continued with regular teaching activities. The cooperation data were collected through a truck racing task using pre-, mid-, post-, and follow-up tests, while the cooperation levels and strategies were evaluated by video observations of role-playing games before and after the tests. The results indicated significant improvements in cooperation scores in both the truck racing task and role-playing games in the experimental group compared to the baseline, with no similar enhancements observed in the control group. Furthermore, cooperation scores in the follow-up were higher than pre- and post-test scores, demonstrating the CCP’s effectiveness in fostering child cooperation, transferability to other contexts, and sustainability. These findings suggest that CCP intervention based on Anji Play can significantly enhance cooperation in children, offering a valuable tool for educational practices. Full article

In recent years, remotely controlling an unmanned aerial vehicle (UAV) to perform coverage search missions has become increasingly popular due to the advantages of the UAV, such as small size, high maneuverability, and low cost. However, due to the distance limitations of the remote control and endurance of a UAV, a single UAV cannot effectively perform a search mission in various and complex regions. Thus, using a group of UAVs to deal with coverage search missions has become a research hotspot in the last decade. In this paper, a differential evolution (DE)-based multi-UAV cooperative coverage algorithm is proposed to deal with the coverage tasks in different regions. In the proposed algorithm, named DECSMU, the entire coverage process is divided into many coverage stages. Before each coverage stage, every UAV automatically plans its flight path based on DE. To obtain a promising flight trajectory for a UAV, a dynamic reward function is designed to evaluate the quality of the planned path in terms of the coverage rate and the energy consumption of the UAV. In each coverage stage, an information interaction between different UAVs is carried out through a communication network, and a distributed model predictive control is used to realize the collaborative coverage of multiple UAVs. The experimental results show that the strategy can achieve high coverage and a low energy consumption index under the constraints of collision avoidance. The favorable performance in DECSMU on different regions also demonstrate that it has outstanding stability and generality. Full article

This study proposes a guidance strategy based on human–machine transition (HMT) for cooperative adaptive cruise control (CACC) truck platoon actuator failures. Existing research on the CACC platoon mainly focuses on upper-level planning and rarely considers platoon planning failures caused by actuator failures. This study proposes that the truck in the platoon creates sufficient space on the target lane through HMT when the actuator fails, thereby promoting lane changes for the entire team. The effectiveness of the proposed strategy is evaluated using the Simulation of Urban Mobility (SUMO) simulation. The results demonstrate that under conditions ensuring the normal operation of traffic flow, this guidance strategy enhances the platoon’s lane-changing capability. In addition, this strategy exhibits stronger robustness and efficiency in different traffic densities. This guidance strategy provides valuable insights into improving the driving efficiency of CACC truck platoons in complex road environments. Full article

Cyber-security research on networked multi-sensor systems is crucial due to the vulnerability to various types of cyberattacks. For the development of effective defense measures, attention is required to gain insight into the complex characteristics and behaviors of cyber attacks from the attacker’s perspective. This paper aims to tackle the problem of distributed consensus estimation for networked multi-sensor systems subject to hybrid attacks and missing measurements. To account for both random denial of service (DoS) attacks and false data injection (FDI) attacks, a hybrid attack model on the estimator-to-estimator communication channel is presented. The characteristics of missing measurements are defined by random variables that satisfy the Bernoulli distribution. Then a modified consensus-based distributed estimator, integrated with the characteristics of hybrid attacks and missing measurements, is presented. For reducing the computational complexity of the optimal distributed estimation method, a scalable suboptimal distributed consensus estimator is designed. Sufficient conditions are further provided for guaranteeing the stability of the proposed suboptimal distributed estimator. Finally, a simulation experiment on aircraft tracking is executed to validate the effectiveness and feasibility of the proposed algorithm. Full article