Results 81 to 90 of about 3,499,518 (292)
Research on State Estimation Method Applied to Trajectory Prediction of Air Platforms Active Defense Operations [PDF]
Hangkong bingqiStarting with the actual operational requirements of active defense, this paper analyzes the advantages, disadvantages, and usage scenarios of different trajectory prediction methods, also analyzes the differences between the active defense combat ...
Lü Mingyuan, Wu Zhen, Qiao Yaobin
doaj +1 more source
Arthritis Care &Research, EarlyView.Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo +2 more
wiley +1 more source
Domain analysis for Reusable Trajectory Simulation
, 2005 Trajectory simulations can be regarded as computational tools to calculate the flight path and other flight parameters of munitions. They have a wide range of uses from concept formation to training simulator construction throughout the lifecycle of a ...
Durak, Umut +2 more
core +1 more source
A Novel Collision Avoidance Logic for Unmanned Aerial Vehicles Using Real-Time Trajectory Planning [PDF]
, 2014 An effective collision avoidance logic should prevent collision without excessive alerting. This requirement would be even more stringent for an automatic collision avoidance logic, which is probably required by Unmanned Aerial Vehicles to mitigate ...
Lai, Chi Kin
core +4 more sources
Parachute-Payload System Flight Dynamics and Trajectory Simulation
International Journal of Aerospace Engineering, 2012 The work traces a general procedure for the design of a flight simulation tool still representative of the major flight physics of a parachute-payload system along decelerated trajectories. An example of limited complexity simulation models for a payload
Giorgio Guglieri
doaj +1 more source
Simulation of the deflected cutting tool trajectory in complex surface milling [PDF]
, 2011 Since industry is rapidly developing, either locally or globally, manufacturers witness harder challenges due to the growing competitivity. This urges them to better consider the four factors linked to production and output: quality, quantity, cost and
Baili, Maher +9 more
core +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Physics-Based Vehicle Simulation Using PD Servo
Applied Sciences, 2019 In this paper, we introduce a novel system for physics-based vehicle simulation from input trajectory. The proposed system approximates the physical movements of a real vehicle using a proportional derivative (PD) servo which estimates proper torques for
Daeun Kang +4 more
doaj +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source