scispace - formally typeset
Search or ask a question

What is Impact Time and Angle Control Guidance? 

Settling time
Robustness (evolution)
Tangent
Dynamics (music)
Missile
Best insight from top research papers

Impact Time and Angle Control Guidance (ITACG) is a guidance law that aims to achieve simultaneous control of impact time and impact angle in missile-target engagements. ITACG considers the coupled dynamics among velocity and normal accelerations to achieve cooperation between impact time and impact angle . It utilizes flight velocity control to achieve impact time cooperation, taking into account the coupling effects arising from normal accelerations in the longitudinal and lateral plane. For impact angle cooperation, ITACG is derived based on modified proportional navigation guidance (PNG), considering the velocity variation . The effectiveness of ITACG has been verified through mathematical simulations . Another approach, called Impact Angle Control Guidance (IACG), focuses on controlling the impact angle of the missile. Different variations of IACG have been proposed, including a predefined-time IACG law with robustness against disturbances and uncertainties , a time-dependent IACG law that shapes the look angle as a function of missile-target distance , and a modified finite-time IACG law that achieves finite-time convergence of the impact-angle error . Additionally, an optimal guidance law has been developed to minimize the change rate of pseudo-curvature, allowing for more general cases where the flight path angle may not be small throughout the entire trajectory .

Answers from top 4 papers

More filters
Papers (4)Insight
Journal Article•DOI
Impact Time and Angle Cooperative Guidance for Multiple Unmanned Air Vehicles (UAVs) with Coupled Dynamics Among Velocity and Normal Accelerations
Marie-Louise Leroux
01 Jan 2023-Lecture Notes in Electrical Engineering
The paper proposes an impact time and angle cooperative guidance law for multiple unmanned air vehicles (UAVs) to achieve simultaneous impact time and impact angle cooperation.
Book Chapter•DOI
A Modified Finite-Time Guidance Law with Impact Angle Constraint
Tsering, Tenzin
01 Jan 2023
The provided paper does not specifically mention "Impact Time and Angle Control Guidance."
Journal Article•DOI
Three-dimensional predefined-time impact angle control guidance law with field-of-view limit
Jian Wang, Xizi Tao, Wei Dong, Chunyan Wang 
01 Aug 2023-Journal of The Franklin Institute-engineering and Applied Mathematics
The paper does not explicitly define "Impact Time and Angle Control Guidance."
Book Chapter•DOI
An Impact Angle Control Guidance via Self-restrained Look Angle Shaping
james
01 Jan 2023
The provided paper does not specifically mention "Impact Time and Angle Control Guidance."

Related Questions

What is impact?5 answers"Impact" can refer to various concepts based on the contexts provided. In the realm of materials science, the Interaction of Materials with Particles and Components Testing (IMPACT) facility allows for the study of surface modifications under energetic particle beams, offering in-depth diagnostics and real-time erosion monitoring. Additionally, in the field of remote sensing and GIS, IMPACT is a tool that streamlines the process of generating land cover maps from Earth Observation data, catering to both ICT users and RS experts through a user-friendly interface and a combination of remote sensing technologies. Furthermore, in the domain of control systems, IMPACT is a CAD-program designed for interactive access to control systems theory algorithms, suitable for both students and control scientists, with a focus on portability and coded in ADA.
How time constraints influence the decision making]?5 answersTime constraints have been found to have a significant impact on decision-making processes. Under high time pressure, individuals tend to make more risky choices and exhibit shorter decision times. This is observed in various domains, including financial markets, where fast decisions can lead to reduced decision quality and increased investment risk. However, the relationship between decision time and profits is not linear, with an optimal threshold value for maximizing returns. Time constraints also affect information search and decision-making, leading to faster decisions but with few differences in search behaviors. In the context of soccer expertise, time constraints and opponent pressure influence decision quality, with time constraints improving decision-making but opponent pressure negatively affecting it. Additionally, time constraints can affect the disposition effect in financial decision-making, with higher time pressure reducing the disposition effect.
How does guidance effect the design proces?5 answersGuidance plays a crucial role in the design process, offering support to designers and helping them create effective and successful solutions. Designers can benefit from systematic design tools such as guidelines, which enhance effectiveness and efficiency in design management, evaluation, and education. These tools can be useful not only for experienced professionals but also for novice designers, providing them with valuable assistance. Usability is a key factor in the acceptance and use of design guidelines, with visually appealing presentations and easy access being important considerations. Additionally, guidance design features in information systems, such as decisional guidance and explanations, have been extensively researched, leading to the development of an integrated taxonomy that allows for systematic comparison and future research opportunities. Overall, guidance in the design process helps designers navigate complex challenges, measure processes, and compare strategies, ultimately leading to improved design outcomes.
What is the effect of estimation on the integrated missile guidance and control systems?3 answersEstimation plays a crucial role in integrated missile guidance and control systems. It allows for the estimation of disturbances and parametric uncertainties present in the system, which helps in improving the interception performance. Disturbance observers are used to estimate the lumped disturbances in each loop, enabling the system to handle disturbances and uncertainties effectively. Additionally, estimation techniques such as moving horizon estimation (MHE) are employed to solve the problem of state estimation in the presence of measurement noise. These estimation methods contribute to the overall stability and robustness of the integrated guidance and control system, ensuring accurate and efficient control commands are generated.
What's the difference between immediate and delayed feedback?in motor learning?3 answersImmediate feedback refers to receiving feedback on one's actions immediately after performing them, while delayed feedback involves a temporal delay between the action and the feedback. In the context of motor learning, several studies have examined the effects of immediate and delayed feedback on acquisition and retention of motor tasks. One study found that subjects who received delayed feedback after a certain number of trials were less accurate during acquisition but more accurate during retention compared to those who received immediate feedback. Another study showed that delayed feedback led to superior retention performance compared to immediate feedback when additional practice was provided. These findings suggest that delayed feedback may enhance long-term retention of motor skills. Additionally, neuroimaging studies have implicated different brain mechanisms in the processing of immediate and delayed feedback, with the striatum involved in immediate feedback processing and the medial temporal lobe (MTL) involved in delayed feedback processing.
What's the difference between real-time, immediate and delayed feedback?5 answersReal-time feedback refers to receiving information or data immediately as it happens, allowing for immediate response or action. Immediate feedback is similar to real-time feedback, providing information or data without any delay, but it may not necessarily be in real-time. It can be given right after an event or action has occurred. Delayed feedback, on the other hand, involves a time delay between an event or action and the feedback received. This delay can be due to various factors, such as waiting for conversions to happen or waiting for a set period of time before training on data. Delayed feedback can introduce challenges, such as fake negatives or inaccurate labeling, but approaches like adaptive waiting windows and online transfer learning can help address these issues.

See what other people are reading

Can reinforcement learning be used to improve decision-making processes in complex systems such as autonomous vehicles or financial markets?
5 answers
Reinforcement learning (RL) is a valuable tool for enhancing decision-making in intricate systems like autonomous vehicles and financial markets. RL methods, which do not heavily rely on model assumptions, have been successfully applied in finance for tasks such as portfolio optimization, optimal execution, and market making. However, challenges like designing reward functions in noisy environments can be mitigated by imitation learning (IL) algorithms, which learn from expert demonstrations to improve decision-making processes. Moreover, innovative frameworks like Cognitive Escape Reinforcement Learning (CERL) have been introduced to address issues like local optima trapping and weak generalization, showcasing superior performance in decision-making tasks such as visual navigation. Additionally, in safety-critical domains like autonomous driving, constrained adversarial reinforcement learning approaches have been proposed to ensure robust decision-making against environmental uncertainties, demonstrating effectiveness in highway on-ramp merging scenarios.What is value of pre existing knowledge?
5 answers
Pre-existing knowledge holds significant value in various domains. In the realm of machine learning, leveraging prior knowledge through informed pre-training on condensed knowledge prototypes enhances learning speed, generalization capabilities, and model robustness. In the educational context, understanding correlations between students' past performance can shed light on their ability to apply acquired knowledge in future studies. Moreover, in the field of medical education, pre-existing knowledge of CPR guidelines among 6th-year medical students positively influences their training outcomes, with those possessing prior knowledge showing higher levels of improvement post-training. Therefore, pre-existing knowledge acts as a foundation that can significantly impact learning outcomes and skill development across various disciplines.What is reliability in electrical engineering?
5 answers
Reliability in electrical engineering refers to the ability of electrical components and systems to function without failure. In the power industry, reliability engineering has become crucial for decision-making, emphasizing the importance of reliable electrical power systems. Power electronics play a significant role in energy systems, impacting security, safety, efficiency, and cost, making the reliability of electronic components and converters vital for overall system reliability. Predicting reliability indices involves analyzing temperature fields of power semiconductor devices, where factors like ambient temperature and dimensional orientation affect failure rates. To enhance power system security and reliability, tools like graph theory-based methodologies are developed for classifying bus reliability based on plant engagement, aiding in mitigating blackout risks. Reliability testing is essential to investigate failure mechanisms and ensure robustness in components and converters.What is multimodal learning?
4 answers
Multimodal learning involves learning across various input modalities like video, audio, and text. It explores how models adapt when the modalities differ between training and deployment, a common scenario in applications involving hardware platforms. This field addresses challenges in utilizing diverse data sources for intelligent agent design, encompassing linguistic, acoustic, visual, tactile, and physiological information. Techniques like multimodal robustness frameworks and deep hierarchical multimodal metric learning have been developed to enhance learning outcomes by leveraging multiple modalities effectively. Despite facing obstacles like noise and lack of information, multimodal learning models have shown promise in improving learning outcomes and teaching effectiveness, especially in open learning environments.How drone motor control delay affect performances?
5 answers
Drone motor control delay significantly impacts performance. Studies show that delays of up to 1.2 seconds can be handled by controllers without adaptive tuning, but longer delays lead to decreased gains and slower mission completion. Human performance degradation is noticeable with delays as low as 100 ms, with delays of 250-300 ms making airplane handling qualities unacceptable. A new control structure for fully actuated systems addresses regulation and trajectory tracking by canceling current disturbances with estimated delayed disturbances, enhancing disturbance attenuation. Time delay dynamics in UAV controller design affect trajectory generation, with delays increasing dynamics impact, especially in vision-based navigation systems. Considering time delays in controller design leads to more stable systems and improved tracking accuracy, crucial for optimal drone performance.What is mismatched disturbance?
5 answers
Mismatched disturbance refers to disturbances in a system that are not accounted for or directly measured in the control design, leading to potential performance degradation or instability. In the context of vehicle platoons and power converters, mismatched disturbances such as velocity and acceleration disturbances in platoons, uncertainties in DC-DC boost converters, and load mutations in solar electric vehiclesare considered. Strategies like finite-time disturbance observers, robust H∞ control with mismatched disturbance compensation, and repetitive control with mismatched disturbance observers are proposed to estimate and counteract these disturbances, enhancing system robustness and performance. These approaches aim to mitigate the impact of mismatched disturbances on system stability and control effectiveness.How has neural network been applied in the epidemiology compartment model of COVID-19 ?
10 answers
Neural networks have been innovatively applied to enhance the epidemiological compartment models of COVID-19, addressing some of the traditional models' limitations and improving prediction accuracy and robustness. Specifically, a deep learning approach utilizing a multi-variate Long Short-term Memory (LSTM) recurrent neural network has been proposed to predict future COVID-19 infection cases and deaths with improved predictive performance by incorporating mobility data and training on multiple time series samples simultaneously. This approach offers fine geographic granularity in predictions and reduces data requirements and computational intensity by substituting a single model for multiple models in an ensemble model, demonstrating similar accuracy and spatial patterns with standard ensemble models used as benchmarks. Furthermore, neural networks have been applied through a deep recurrent reinforced learning-based model to evaluate and predict the spatiotemporal effects of various control measures on COVID-19 cases and mortality. This model uses a combination of control measures, official statistics, and government data to closely match actual values of cases and mortality, highlighting the importance of adjunctive measures such as international travel and quarantine restrictions. Additionally, machine learning techniques, including neural networks, have been employed to project COVID-19 infections and deaths, comparing traditional time series statistical models with modern machine learning approaches. This research identifies the logistic growth model as the best fit for the pandemic's behavior in Mexico, emphasizing the correlation of climate and mobility variables with disease numbers and proposing a model to predict daily cases and fatalities using time series data, mobility, and weather variables. These applications of neural networks in epidemiological compartment models of COVID-19 represent a significant advancement in the field, offering more accurate, robust, and geographically detailed predictions that can better inform public health decisions and interventions.How to improve performances in Graph Convolutional Network?
5 answers
To enhance performance in Graph Convolutional Networks (GCNs), various strategies have been proposed. One approach involves utilizing t-hopGCN to describe t-hop neighbors by the shortest path between nodes, enhancing node classification on graphs without node features. Another method restricts polynomial coefficients in spectral filters to prevent overfitting, significantly improving GCN performance in large receptive fields and across datasets. Additionally, incorporating wavelet denoising filters into GCNs unifies different architectures under a common framework, offering a trade-off between local and global information for improved performance on diverse datasets. Furthermore, the deep graph convolutional generative adversarial network (DGCGAN) combines GCN and DCGAN to address non-robustness and low accuracy issues, outperforming baselines in semi-supervised node classification and image classification tasks.What is fluid dynamics?
5 answers
Fluid dynamics is the study of the behavior of liquids and gases in motion. Fluids, which include liquids, gases, vapors, and plasmas, have the ability to flow and take the shape of their container. This field of science interacts with various disciplines like astronomy, meteorology, oceanography, and engineering, impacting areas such as blood circulation and industrial processes. Fluid mechanics, a branch of physics, delves into the properties and behavior of fluids, discussing dimensionless numbers and transport properties crucial in understanding fluid dynamics. Momentum transfer in fluid dynamics influences mass transfer, heat transfer, mixing, and homogenization, playing a significant role in processes like metal extraction and refining. Fluid dynamics is essential for comprehending how fluids move and behave in both natural and industrial settings, with potential future applications across various scientific and industrial domains.Does placement of IMU impact accuracy when measuring movemente?
5 answers
The placement of Inertial Measurement Units (IMUs) significantly impacts the accuracy when measuring movements. Research highlights that variations in sensor attachment locations can lead to differences in the accuracy of measuring joint angles and gait parameters. Studies emphasize the necessity to reevaluate sensor systems and algorithms when the sensor position changes to maintain reliability in monitoring systems. Different sensor positions on the body can result in varying bias and root mean square error values, affecting the precision of IMU-based kinematic measurements for different functional movements. Therefore, optimizing IMU placement is crucial for accurate joint angle estimation and gait analysis, especially in clinical settings where IMUs are used for diagnosing and rehabilitating gait pathologies.How does optical camera communication differ from other forms of communication in IoV systems?
5 answers
Optical camera communication (OCC) in the Internet of Vehicles (IoV) systems stands out due to its utilization of image sensors for data reception, offering spatial separation properties and robustness to ambient noise, making it ideal for outdoor applications like intelligent transportation systems (ITSs). OCC, a form of visible light communication, leverages commercial off-the-shelf devices, providing a wide range of services in various areas such as intelligent transportation, indoor positioning, and the Internet of Things (IoT). By integrating Color Shift Keying modulation with the Rolling Shutter mechanism, OCC can achieve higher data rates compared to other modulation schemes, making it a promising technology for wireless communication. Additionally, OCC systems have been experimentally demonstrated to achieve high data rates, such as 150 kbit/s, using innovative transmitter designs.