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Adaptive critic learning for approximate optimal event-triggered tracking control of nonlinear systems with prescribed performances
T Wang, L Zhang, N Xu, KH Alharbi - International Journal of …, 2024 - Taylor & Francis
This paper studies the approximate optimal event-triggered tracking control problem for a
class of second-order nonlinear systems with prescribed performances. By employing a …
class of second-order nonlinear systems with prescribed performances. By employing a …
Formation control scheme with reinforcement learning strategy for a group of multiple surface vehicles
This article presents a comprehensive approach to integrate formation tracking control and
optimal control for a fleet of multiple surface vehicles (SVs), accounting for both kinematic …
optimal control for a fleet of multiple surface vehicles (SVs), accounting for both kinematic …
Safe exploration in model-based reinforcement learning using control barrier functions
This paper develops a model-based reinforcement learning (MBRL) framework for learning
online the value function of an infinite-horizon optimal control problem while obeying safety …
online the value function of an infinite-horizon optimal control problem while obeying safety …
Temporal logic guided safe model-based reinforcement learning: A hybrid systems approach
This paper studies the problem of synthesizing control policies for uncertain continuous-time
nonlinear systems from linear temporal logic (LTL) specifications using model-based …
nonlinear systems from linear temporal logic (LTL) specifications using model-based …
Approximate optimal indirect regulation of an unknown agent with a Lyapunov-based deep neural network
An approximate optimal policy is developed for a pursuing agent to indirectly regulate an
evading agent coupled by an unknown interaction dynamic. Approximate dynamic …
evading agent coupled by an unknown interaction dynamic. Approximate dynamic …
Target tracking subject to intermittent measurements using attention deep neural networks
This letter presents a novel estimator and predictor framework for target tracking applications
that estimates the pose of a mobile target that intermittently leaves the field-of-view (FOV) of …
that estimates the pose of a mobile target that intermittently leaves the field-of-view (FOV) of …
Modular adaptive safety-critical control
This paper presents an adaptive control approach for uncertain nonlinear systems subject to
safety constraints that allows for modularity in the selection of the parameter estimation …
safety constraints that allows for modularity in the selection of the parameter estimation …
Approximate Optimal Indirect Control of an Unknown Agent Within a Dynamic Environment Using a Lyapunov-Based Deep Neural Network
An optimal control policy is derived for an indirect herding control problem in an environment
with moving obstacles. A herding agent is tasked with influencing a target agent toward a …
with moving obstacles. A herding agent is tasked with influencing a target agent toward a …
A Collision‐Free Pursuit‐Evasion Framework for Indirect Herding and Formation Control of Noncooperative UAVs
Y Zhang, Y Zhu, M Tan, J Wang - International Journal of …, 2025 - Wiley Online Library
In this article, we aim to design a general framework for the pursuit‐evasion (PE) game of
multiple UAVs. Based on the distance between the pursuers and the evader, the whole …
multiple UAVs. Based on the distance between the pursuers and the evader, the whole …
Formation Control of Multiple Unmanned Aerial Vehicle Systems using Integral Reinforcement Learning
NT Dang, QN Duong - Journal of Robotics and Control (JRC), 2024 - journal.umy.ac.id