Reinforcement learning-based optimal tracking control of an unknown unmanned surface vehicle
In this article, a novel reinforcement learning-based optimal tracking control (RLOTC)
scheme is established for an unmanned surface vehicle (USV) in the presence of complex …
scheme is established for an unmanned surface vehicle (USV) in the presence of complex …
Reinforcement learning-based finite-time tracking control of an unknown unmanned surface vehicle with input constraints
N Wang, Y Gao, C Yang, X Zhang - Neurocomputing, 2022 - Elsevier
In this paper, subject to completely unknown system dynamics and input constraints, a
reinforcement learning-based finite-time trajectory tracking control (RLFTC) scheme is …
reinforcement learning-based finite-time trajectory tracking control (RLFTC) scheme is …
Model-reference reinforcement learning for collision-free tracking control of autonomous surface vehicles
This paper presents a novel model-reference reinforcement learning algorithm for the
intelligent tracking control of uncertain autonomous surface vehicles with collision …
intelligent tracking control of uncertain autonomous surface vehicles with collision …
Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle
N Wang, Y Gao, X Zhang - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
An unmanned surface vehicle (USV) under complicated marine environments can hardly be
modeled well such that model-based optimal control approaches become infeasible. In this …
modeled well such that model-based optimal control approaches become infeasible. In this …
Target tracking control of UAV through deep reinforcement learning
B Ma, Z Liu, W Zhao, J Yuan, H Long… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This study presents an innovative reinforcement-learning-based control algorithm for a
vertical take-off and landing (VTOL) aircraft under wind disturbances. In our approach, the …
vertical take-off and landing (VTOL) aircraft under wind disturbances. In our approach, the …
Multi-agent reinforcement learning aided intelligent UAV swarm for target tracking
Past few years have witnessed the widespread adoption of unmanned aerial vehicles
(UAVs) in target tracking for regional monitor and strike. Most existing target tracking …
(UAVs) in target tracking for regional monitor and strike. Most existing target tracking …
Target tracking control of a biomimetic underwater vehicle through deep reinforcement learning
In this article, the underwater target tracking control problem of a biomimetic underwater
vehicle (BUV) is addressed. Since it is difficult to build an effective mathematic model of a …
vehicle (BUV) is addressed. Since it is difficult to build an effective mathematic model of a …
Multi pseudo Q-learning-based deterministic policy gradient for tracking control of autonomous underwater vehicles
This paper investigates trajectory tracking problem for a class of underactuated autonomous
underwater vehicles (AUVs) with unknown dynamics and constrained inputs. Different from …
underwater vehicles (AUVs) with unknown dynamics and constrained inputs. Different from …
Model-based deep reinforcement learning for data-driven motion control of an under-actuated unmanned surface vehicle: Path following and trajectory tracking
Unmanned surface vehicles (USVs) are a promising marine robotic platform for numerous
potential applications in ocean space due to their small size, low cost, and high autonomy …
potential applications in ocean space due to their small size, low cost, and high autonomy …
Path planning for UAV ground target tracking via deep reinforcement learning
B Li, Y Wu - IEEE access, 2020 - ieeexplore.ieee.org
In this paper, we focus on the study of UAV ground target tracking under obstacle
environments using deep reinforcement learning, and an improved deep deterministic policy …
environments using deep reinforcement learning, and an improved deep deterministic policy …
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